Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data

Abstract

Abstract:The objective of this study was to investigate the tempo-spatial distribution of paddy rice in Northeast China using moderate resolution imaging spectroradiometer (MODIS) data. We developed an algorithm for detection and estimation of the transplanting and flooding periods of paddy rice with a combination of enhanced vegetation index (EVI) and land surface water index with a central wavelength at 2 130 nm (LSWI 2130 ). In two intensive sites in Northeast China, fine resolution satellite imagery was used to validate the performance of the algorithm at pixel and 3×3 pixel window levels, respectively. The commission and omission errors in both of the intensive sites were approximately less than 20%. Based on the algorithm, annual distribution of paddy rice in Northeast China from 2001 to 2009 was mapped and analyzed. The results demonstrated that the MODIS-derived area was highly correlated with published agricultural statistical data with a coefficient of determination (R 2 ) value of 0.847. It also revealed a sharp decline in 2003, especially in the Sanjiang Plain located in the northeast of Heilongjiang Province, due to the oversupply and price decline of rice in 2002. These results suggest that the approaches are available for accurate and reliable monitoring of rice cultivated areas and variation on a large scale.

Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series

“…Our maps are able to show detailed shifts in rice area on the local to county scale, which could not be deduced from the publicly-available agricultural statistics. The biggest observable change during the time period studied is the large increase in rice area in Heilongjiang, which has also been reported by previous studies [36,38,40,42]. From 2005 onward, paddy rice area in Heilongjiang increased at an unprecedented rate.…”

Evolution of regional to global paddy rice mapping methods: A review

“…Based on this approach, continental scale paddy rice maps was generated, covering southern China, South Asia, and Southeast Asia by using 8-day time series MODIS data (Xiao et al, 2006(Xiao et al, , 2005. This method has attracted increasing attention and is now widely used in various geographical regions (Dong et al, , 2016a(Dong et al, , 2016bQin et al, 2015;Shi et al, 2013;Zhang et al, 2015).…”

“…Several studies have attempted to improve the phenology-based rice mapping method (Xiao et al, 2005) by defining the flooding and transplanting periods based on observed phenology data from agricultural meteorological stations (Peng, 2009;Peng et al, 2011;Shi et al, 2013). The dependence of these improved methods on agricultural phenology data limited the approach's extensive applications in the regions without observations.…”

Uji Model Fase Pertumbuhan Padi Berbasis Citra Modis Multiwaktu Di Pulau Lombok (The Testing of Phase Growth Rice Model Based on Multitemporal Modis in Lombok Island)

“…Huamin et al, (2009) menggunakan citra MODIS untuk melihat dinamika musiman indek vegetasi dan karakteristik fenologi gandum dan jagung di China. Shi et al, (2013) (Xiao et al, 2005). Namun, penggunaan citra satelit resolusi spasial moderat dan global telah dibatasi terutama di lahan sawah yang kecil/sempit, karena ada banyak jenis tutupan lahan dalam satu pixel.…”

“…Metode yang digunakan dalam penelitian ini adalah metode analisis citra MODIS delapan harian meliputi ektraksi indeks (EVI), filter/smoothing dengan metode rata-rata bergerak (moving average) dan median filter (Shi et al, 2013) kemudian pemetaan fase pertumbuhan (sebelum dan setelah smoothing). Selain itu juga dilakukan klasifikasi penutupan/ penggunaan lahan pada citra LANDSAT 8 multiwaktu untuk memperoleh fase pertumbuhan padi (Tabel 3-1) untuk analisis akurasi fase pertumbuhan berbasis MODIS tahap I, sedangkan analisis akurasi tahap II (input hasil model yang tidak di-smoothing) dan III (input hasil model yang di-smoothing).…”