Natural tropical rainforests in China’s Xishuangbanna region have undergone dramatic conversion to rubber plantations in recent decades, resulting in altering the region’s environment and ecological systems. Therefore, it is of great importance for local environmental and ecological protection agencies to research the distribution and expansion of rubber plantations. The objective of this paper is to monitor dynamic changes of rubber plantations in China’s Xishuangbanna region based on multitemporal Landsat images (acquired in 1989, 2000, and 2013) using a C5.0-based decision-tree method. A practical and semiautomatic data processing procedure for mapping rubber plantations was proposed. Especially, haze removal and deshadowing were proposed to perform atmospheric and topographic correction and reduce the effects of haze, shadow, and terrain. Our results showed that the atmospheric and topographic correction could improve the extraction accuracy of rubber plantations, especially in mountainous areas. The overall classification accuracies were 84.2%, 83.9%, and 86.5% for the Landsat images acquired in 1989, 2000, and 2013, respectively. This study also found that the Landsat-8 images could provide significant improvement in the ability to identify rubber plantations. The extracted maps showed the selected study area underwent rapid conversion of natural and seminatural forest to a rubber plantations from 1989 to 2013. The rubber plantation area increased from 2.8% in 1989 to 17.8% in 2013, while the forest/woodland area decreased from 75.6% in 1989 to 44.8% in 2013. The proposed data processing procedure is a promising approach to mapping the spatial distribution and temporal dynamics of rubber plantations on a regional scale.
Vegetation biomass is an important ecological variable for understanding responses to the climate system and currently
observed global change. It is also an important factor influencing biodiversity and environmental processes, especially in
semi-arid areas. These areas cover large parts of the land surface and are especially susceptible to degradation and
desertification. Therefore, a great need exists for the development of accurate and transferable methods for biomass
estimation in semi-arid areas. This paper presents an overview of previously applied remote sensing based approaches
for above-ground biomass estimation in semi-arid regions. Based on the literature analysis a summary and discussion of
commonly observed difficulties and challenges will be presented. Further research is especially required on the
transferability of remote sensing based methods for biomass estimation in semi-arid areas. Additional analyses should be
directed towards efficient field sampling schemes, and the synergetic use of optical and radar data.