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Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine

Di, Yuanyuan and Zhang, Geli and You, Nanshan and Yang, Tong and Zhang, Qiang and Liu, Ruoqi and Doughty, Russell B. and Zhang, Yangjian (2021) Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine. Remote Sensing, 13 (12). Art. No. 2289. ISSN 2072-4292. doi:10.3390/rs13122289. https://resolver.caltech.edu/CaltechAUTHORS:20210623-164126874

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Abstract

The Tibetan Plateau (TP), known as “The Roof of World”, has expansive alpine grasslands and is a hotspot for climate change studies. However, cropland expansion and increasing anthropogenic activities have been poorly documented, let alone the effects of agricultural activities on food security and environmental change in the TP. The existing cropland mapping products do not depict the spatiotemporal characteristics of the TP due to low accuracies and inconsistent cropland distribution, which is affected by complicated topography and impedes our understanding of cropland expansion and its associated environmental impacts. One of the biggest challenges of cropland mapping in the TP is the diverse crop phenology across a wide range of elevations. To decrease the classification errors due to elevational differences in crop phenology, we developed two pixel- and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth Engine platform along the Brahmaputra River and its two tributaries (BRTT) in the Tibet Autonomous Region, also known as the granary of TP, in 2015–2019. Our first phenology-based cropland mapping algorithm (PCM1) used different thresholds of land surface water index (LSWI) by considering varied crop phenology along different elevations. The second algorithm (PCM2) further offsets the phenological discrepancy along elevational gradients by considering the length and peak of the growing season. We found that PCM2 had a higher accuracy with fewer images compared with PCM1. The number of images for PCM2 was 279 less than PCM1, and the Matthews correlation coefficient for PCM2 was 0.036 higher than PCM1. We also found that the cropland area in BRTT was estimated to be 1979 ± 52 km2 in the late 2010s. Croplands were mainly distributed in the BRTT basins with elevations of 3800–4000 m asl. Our phenology-based methods were effective for mapping croplands in mountainous areas. The spatially explicit information on cropland area and distribution in the TP aid future research into the effects of cropland expansion on food security and environmental change in the TP.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3390/rs13122289DOIArticle
ORCID:
AuthorORCID
Di, Yuanyuan0000-0002-9739-1882
Zhang, Geli0000-0002-0386-5646
Yang, Tong0000-0002-3442-400X
Zhang, Qiang0000-0001-8389-4713
Liu, Ruoqi0000-0003-1704-1151
Doughty, Russell B.0000-0001-5191-2155
Additional Information:© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Received: 7 May 2021; Revised: 3 June 2021; Accepted: 7 June 2021; Published: 11 June 2021. This work was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0608) and the 2115 Talent Development Program of China Agricultural University. Author Contributions: Y.D. and G.Z. designed the research; Y.D., N.Y. and G.Z. analyzed data; Y.D. and G.Z. designed figures; all authors contributed to the results interpretation and discussion; Y.D. and G.Z. led the writing of the manuscript with input from N.Y., T.Y., Q.Z., R.L., R.B.D. and Y.Z. All authors have read and agreed to the published version of the manuscript. Data Availability Statement: The cropland maps in this study can be accessible from the corresponding author upon request. The authors declare no conflict of interest.
Funders:
Funding AgencyGrant Number
Second Tibetan Plateau Scientific Expedition and Research Program2019QZKK0608
China Agricultural UniversityUNSPECIFIED
Subject Keywords:cropland; Tibetan Plateau; pixel- and phenology-based algorithm; Google Earth Engine; Landsat
Issue or Number:12
DOI:10.3390/rs13122289
Record Number:CaltechAUTHORS:20210623-164126874
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210623-164126874
Official Citation:Di, Y.; Zhang, G.; You, N.; Yang, T.; Zhang, Q.; Liu, R.; Doughty, R.B.; Zhang, Y. Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine. Remote Sens. 2021, 13, 2289. https://doi.org/10.3390/rs13122289
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109554
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Jun 2021 17:53
Last Modified:23 Jun 2021 17:53

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