Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation.

Hao Chen,Chao Ding,Xiangnan Liu,Fang Huang

doi:10.3390/s18113676

Abstract

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

Highlights

Land degradation can be recognized as a continuing loss of ecosystem service due to loss of soil fertility, loss of vegetation cover and productivity, soil erosion, change in plant species, and other processes of environmental evolution [1]
We found that the phenological information we extracted was similar to existing studies
This research demonstrated the feasibility of improving the RESTREND by introducing phenological information to remove the influence of precipitation on normalized difference vegetation index (NDVI) for detecting human-induced land degradation

Summary

Introduction

Land degradation can be recognized as a continuing loss of ecosystem service due to loss of soil fertility, loss of vegetation cover and productivity, soil erosion, change in plant species, and other processes of environmental evolution [1]. The rate and extent of land degradation has both reached an astonishing level [3]. Urbanization is one of the most widespread anthropogenic causes of land degradation in recent years [6,7]. Rapid changes in land use and land cover as well as the increased ecosystematic degradation were caused by the increasing rate of urbanization and increasing population in developing cities [8]. Considerable attention is currently being directed towards monitoring changes in the present state of degradation [9]. Such studies are important because the spatial characteristics of land degradation are useful for understanding the various impacts of Sensors 2018, 18, 3676; doi:10.3390/s18113676 www.mdpi.com/journal/sensors

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