Time Tracking of Different Cropping Patterns Using Landsat Images under Different Agricultural Systems during 1990–2050 in Cold China

Tao Pan,Alishir Kurban,Chi Zhang,Rafiq Hamdi,Guoming Du,Wenhui Kuang,Philippe De Maeyer

doi:10.3390/rs10122011

Abstract

Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and associated environmental effects. The Cold China contains different agricultural systems (state and private farming), and such systems could lead to different cropping patterns. So far, such changes have not been revealed yet. Based on the Landsat images, this study tracked cropping information in five-year increments (1990–1995, 1995–2000, 2000–2005, 2005–2010, and 2010–2015) and predicted future patterns for the period of 2020–2050 under different agricultural systems using developed method for determining cropland patterns. The following results were obtained: The available time series of Landsat images in Cold China met the requirements for long-term cropping pattern studies, and the developed method exhibited high accuracy (over 91%) and obtained precise spatial information. A new satellite evidence was observed that cropping patterns significantly differed between the two farm types, with paddy field in state farming expanding at a faster rate (from 2.66 to 68.56%) than those in private farming (from 10.12 to 34.98%). More than 70% of paddy expansion was attributed to the transformation of upland crop in each period at the pixel level, which led to a greater loss of upland crop in state farming than private farming (9505.66 km2 vs. 2840.29 km2) during 1990–2015. Rapid cropland reclamation is projected to stagnate in 2020, while paddy expansion will continue until 2040 primarily in private farming in Cold China. This study provides new evidence for different land use change pattern mechanisms between different agricultural systems, and the results have significant implications for understanding and guiding agricultural system development.

Highlights

Crops are basic requirements for feeding people, and cropping pattern information is important for human health and grain ration security
Large-scale applications of time series Landsat images in cropland change studies beginning in 1990 face various challenges, such as variable image quality and inhomogeneous data availability at spatial and temporal scales
The results demonstrated that the available Landsat images in Cold China met the requirements for long-term cropping pattern studies; and the developed method exhibited high accuracy and good spatial pattern results

Summary

Introduction

Crops are basic requirements for feeding people, and cropping pattern information is important for human health and grain ration security. Cropland expansion has occurred in many places [1,2,3,4], the maintenance of cropland area is still a challenge worldwide [5]. Such issues are prevalent in China, which feeds approximately twenty percent of the global population with no more than seven percent of the world’s cropland [6,7,8]. The rapid expansion of agricultural land in North China has greatly affected the water cycles [11], climate change [12,13], and greenhouse gas emissions [14,15]. Long time series and high precision cropping pattern dataset is needed to study the differential contribution of crops on environment

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Results

Conclusion