Earth Observation Data for Spatio-Temporal Analysis of Land Cover Changes Within Notified Forest Areas

Abstract

AbstractTime-series satellite data provide vital input for effective and accurately monitoring land cover change and assessment of vegetation condition on the land surface. Land cover change can be easily detected by any changes in temporal profile and pattern in long-term EVI data. Snapshot satellite image-based (two-date or multi-date) land cover change detection approach is in existence for quite a long time and is successful, though, snapshot image-based approaches have limitation such as temporal resolution, cloud cover etc. Therefore, in recent time, availability of huge dataset especially long-term satellite data provides the opportunity to study vegetation dynamics and accurately observing natural resources. In this study, analysis of temporal pattern to identify change in land cover based on Wavelet transform (WT) technique and statistical approaches (Mann–Kendall test and Sen slope’s method) in time-series Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data for the period of 2005–2014. The Mann–Kendall (MK) test is used to detect monotonic trends and the Sen’s slope estimate the magnitude of existing trend in long-term EVI data. Multi-temporal MODIS EVI time-series of the MOD13Q1 global products with 250-m spatial resolution was used for the period 2005–2014 and temporal pattern was analyzed to identify change on Earth surface. The results from this study can serve guideline for accurately monitoring and sustainable strategies for conservation of green cover in study area.KeywordsTime seriesEVIWaveletLand cover changeMann–Kendall testSen slope