**South China Tropical Forest Changes in Response to Economic Development and Protection Policies Economic Development and Protection Policies**

**South China Tropical Forest Changes in Response to** 

DOI: 10.5772/intechopen.73296

Shudong Wang and Taixia Wu Shudong Wang and Taixia Wu Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.73296

#### **Abstract**

The destruction of tropical forests continues to attract attention from the international community. China's National Forest Administration has adopted protective measures for tropical forests, and efforts have been developed to balance forest protection and economic development in Hainan Island, China. However, the response of natural tropical forest to local economic development and the effectiveness of forest management and protection policies remain unclear because of complexity of tropical evergreen ecosystems. After comprehensive analysis of spectral characteristics, spatial distribution, patch shape, and other characteristics of main forests, we developed an information extraction method based on the decision tree method, combining digital elevation model (DEM) and forest planning maps, and established flowcharts and processes for sophisticated object-based information extraction. The accuracy of our method was 92%, and the method proved to be applicable and effective in the classification of complex surface features in a tropical evergreen ecosystem. Forces resulting in the change of these forests were explored by analyzing the relationships between economic development, protection policies, as well as environmental factors.

**Keywords:** tropical forest, economic forest, forest management, Hainan Island, remote sensing, GIS, development and protection policies

## **1. Introduction**

Deforestation, especially of natural tropical forests, has attracted international attention as these tropical forests have very high levels of biodiversity [1–4]. Tropical forests mainly occur in developing countries. However, large areas of natural forests have disappeared as a result of continuous human population growth and their economic development. Some protective

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

measures have been adopted, but it is still difficult to prevent the loss of natural tropical forests due to conflicts between economic development and forest protection.

In fact, much auxiliary information could be used. For example, when compared with rubber and pulp plantations, the remotely sensed spectra of natural forest exhibit more differences from December to the following January than it does during other seasons [13]. In addition, remotely sensed images of natural forest, and rubber and pulp plantations each have obvious characteristics related to their distribution, patch shape, and texture. For example, pulp and rubber plantations usually occur in areas where the slope is less than 25°, and rubber planta-

South China Tropical Forest Changes in Response to Economic Development and Protection…

http://dx.doi.org/10.5772/intechopen.73296

117

To overcome the abovementioned challenges, we used an object-oriented, decision tree method to deal with the complex change processes of natural forest, and rubber and pulp plantations for the first time. The overlay technique of GIS was also used to map natural forest, and rubber and pulp plantations during 1988–2008, and to analyze the main factors driving forest change and the relationships between the three forest types. Our objectives were to:

**1.** Map the spatial extent of natural forest, and rubber and pulp plantations, and to analyze

**2.** Assess the relationships between the spatial patterns of multiple forests; identify the main

area has a warm and humid tropical monsoon climate with annual average temperatures ranging from 22 to 26°C. Mountainous areas surround Five Finger Mountain and Yinggeling in Hainan Island. The island's natural tropical forest mainly includes tropical monsoon forest, tropical rain forest, evergreen broad-leaved forest, and coniferous forest. Economic forest mainly includes rubber plantations and orchards, which usually occur in the flatlands at the

in the central part of Hainan Island (**Figure 1**). The study

temporal and spatial succession occurring during 1988 and 2008.

**Figure 1.** The location of the study area (the central Hainan Island in China).

tions often lie at comparatively lower elevations.

factors driving changes.

**2. Materials and methods**

The study area covers 14,000 km2

**2.1. Study area**

In China, the total area of tropical forest is currently increasing because of national reforestation policies, but the proportion of natural tropical forest to economic forest has changed in recent years [5]. As a result, changes have occurred affecting the maintenance of biodiversity, ecological functioning, and stability of forest ecosystem [6–8]. The Hainan Island of China has a large area of tropical forest, which serves as a natural treasure of biodiversity [2]. In recent years, the island has seen rapid economic development. Natural tropical forest is being constantly replaced by economic forest because of increasing demand for rubber, timber, and other forest products since 1988. To develop the economy in a sustainable and ecologically sensitive manner, the local government has proposed various ecological protection measures since 1998. In fact, the tropical forest in Hainan Island has greatly changed because of economic development and protection policies after 1998. Tropical forests are known to be impacted by population growth, economic development, national policies, and natural factors (such as terrain, climate, etc.) [5]. However, the key factors causing the changes of tropical forest remain unclear.

Because the proportion of natural tropical forest to economic forest has changed, two key challenges arise: (1) understanding how and why natural tropical forests are changing, and which factors have led to the changes; (2) understanding the fate and implications of the succession of different forest types. Thus, monitoring the dynamics of those changes occurring in natural tropical forest and economic forest becomes necessary, together with the identification of the main factors leading to those changes over broad spatial and temporal scales.

Brandt et al. recognized that mapping forest distribution and succession are an essential component of forest biodiversity assessment [2]. Remote sensing provides an efficient technique for the monitoring and managing of tropical forests [9]. In addition, a combination of remote sensing and GIS techniques could help scientists discover the intrinsic forces driving the dynamics of forests.

However, some challenges remain in using remote sensing image classification. For example, for vegetation classification, there is a problem with mixed pixels resulting from same objects exhibiting different reflectance at varying wavelengths [10]. Also, it is difficult to improve the precision of the process of extraction without the support of a prior knowledge, such as the spatial distribution of various forests or patch shapes.

In addition, the use of pixel-based methods is tiring and labor-intensive work, and misclassification of pixels is likely to occur because of errors during spectrum analysis [11]. For example, some natural forests lying within shaded areas of mountains tend to be regarded as other land use types. An object-oriented method could segment remote sensing images into different patch sizes based on integrated features of the spectrum, texture, shape of patch, and so forth [12]. In addition, the decision tree method could gradually extract individual land use types, using remote sensing extraction models and relevant auxiliary data, such as the distribution of various forest types.

In fact, much auxiliary information could be used. For example, when compared with rubber and pulp plantations, the remotely sensed spectra of natural forest exhibit more differences from December to the following January than it does during other seasons [13]. In addition, remotely sensed images of natural forest, and rubber and pulp plantations each have obvious characteristics related to their distribution, patch shape, and texture. For example, pulp and rubber plantations usually occur in areas where the slope is less than 25°, and rubber plantations often lie at comparatively lower elevations.

To overcome the abovementioned challenges, we used an object-oriented, decision tree method to deal with the complex change processes of natural forest, and rubber and pulp plantations for the first time. The overlay technique of GIS was also used to map natural forest, and rubber and pulp plantations during 1988–2008, and to analyze the main factors driving forest change and the relationships between the three forest types. Our objectives were to:

