Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data

Chunlei Ma,Bin Ai,Jun Zhao,Wei Huang,Xiaoping Xu

doi:10.3390/rs11080921

Abstract

Mangrove forests are among the most productive ecosystems on Earth and mainly grow at tropical and subtropical latitudes. They provide many important ecological and societal functions. However, rapid spatiotemporal variations in mangroves have been observed worldwide, especially in the coastal zones of developing areas, and the integrity of mangroves has been significantly affected by anthropogenic activities in recent decades. The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution over the past 30 years in Guangdong Province. This goal was achieved by classifying multi-temporal Landsat images using a decision tree method based on Classification and Regression Tree (CART) algorithm. The driving forces resulting in these spatiotemporal variations of mangroves were then discussed. Our analysis revealed that the classification method used in this study yielded good accuracy, with an overall accuracy and kappa coefficient of higher than 90% and 0.8, respectively. In Guangdong province, the mangrove forests covered areas of 9305, 9556, 6793, and 9700 ha in 1985, 1995, 2005, and 2015, respectively, with remarkable inter-annual changes. Mangrove forests are mainly located in Western Guangdong, and few are located in Eastern Guangdong. The distribution of mangrove patches became more fragmented from 1985 to 2005 and less fragmented from 2005 to 2015, and the distribution pattern in 2015 showed stronger connectivity than that in 1985. Natural factors, such as temperature, sea level rise, extreme weather events, and the length of the coastline, have macroscopic effects on the distribution of mangrove forests. Anthropogenic activities, such as deforestation, urbanization, and aquaculture development, have negative effects on the distribution of mangroves. On the other hand, the establishment of nature reserves has positive effects on the distribution of mangroves. The findings of this study provide a reference for the management and protection of mangroves, which is of great practical significance.

Highlights

Mangrove forests are among the most productive ecosystems on Earth and can be found at tropical and subtropical latitudes [1,2,3]
The producer’s accuracy of the mangrove classification was around 93%, 83%, and 81% in Western Guangdong (WG), Pearl River Delta (PRD), and Eastern Guangdong (EG), respectively, and the user’s accuracy was 88%, 97%, and 90%, respectively
The classification results indicated that the incorporation of Normalized Difference Vegetation Index (NDVI), Inundated Mangrove Forest Index (IMFI), and ISODATA data can improve the discrimination between mangrove forests and other land use types

Summary

Introduction

Mangrove forests are among the most productive ecosystems on Earth and can be found at tropical and subtropical latitudes [1,2,3]. In terms of classifying mangroves over large areas at different times, the decision tree classification method based on CART algorithm has shown the ability to obtain classification rules from training samples directly and has the advantage of being independent of the assumptions of value distribution. This method can assess variables independently from one another in contrast to other statistical analysis methods, such as maximum likelihood classification [31]. The decision tree classification method based on CART algorithm was adopted to retrieve the multi-temporal distribution information of mangroves in this study

Objectives

Methods

Results

Discussion

Conclusion