Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations
نویسنده
چکیده
There has been a recent proliferation of remote sensing-based trend analysis for monitoring regional desertification. These show contradictory results. All of them claim to have been “validated” through expert interpretation, in the absence of sufficient field data. We suggest that such an approach is not sufficiently rigorous. Therefore, we demonstrate an approach which simulates land degradation so that the intensity, rate and timing of the reduction in NDVI can be controlled, in order to quantitatively evaluate the ability of methods to detect these known changes. The results show that linear trend analysis is rather insensitive to previously observed levels of NDVI reduction due to degradation in the well-studied communal lands in the Lowveld of South Africa. The period of investigation, has a large but rather unpredictable influence on the linear trends. This casts doubts over the ability of linear trend analysis, to detect relatively subtle, slowly-developing degradation in semi-
منابع مشابه
Evaluation of land degradation trend using satellite imagery and climatic data (Case study: Fars province)
Introduction: Climate change and human activities have a direct impact on land vegetation. Decreased rainfall and increased temperature are among the climate change factors leading to significant changes in water resources and energy balance in affected areas. On the other hand, human activities such as growing population, overgrazing and land use changes that make change in land conditions, al...
متن کاملLand Degradation Assessment Using Residual Trend Analysis of GIMMS NDVI3g, Soil Moisture and Rainfall in Sub-Saharan West Africa from 1982 to 2012
Areas affected by land degradation in Sub-Saharan West Africa between 1982 and 2012 are identified using time-series analysis of vegetation index data derived from satellites. The residual trend (RESTREND) of a Normalized Difference Vegetation Index (NDVI) time-series is defined as the fraction of the difference between the observed NDVI and the NDVI predicted from climate data. It has been wid...
متن کاملRainfall variability and vegetation dynamics in the Mauritanian Sahel
To evaluate the state of ecosystems in Mauritania, rainfall time series and a GIMMSNDVI (global inventory modeling and mapping study-normalized difference vegetation index) data set were used for analysis of rainfall and NDVI trends and their relationships in different ecological zones. Linear regression analysis and the non-parametric Mann-Kendall test were applied to detect NDVI and rainfall ...
متن کاملDetecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset
This study proposed a multi-target hierarchical detection (MTHD) method to simultaneously and automatically detect multiple directional land cover changes. MTHD used a hierarchical strategy to detect both abrupt and trend land cover changes successively. First, Grubbs’ test eliminated short-lived changes by considering them outliers. Then, the Brown-Forsythe test and the combination of Tomé’s m...
متن کاملSpatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling
Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the ...
متن کامل