Mapping Grassland Based on Bio-Climate Probability and Intra-Annual Time-Series Abundance Data of Vegetation Habitats
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Published:2023-09-27
Issue:19
Volume:15
Page:4723
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Sun Minxuan12, Ji Zhengxin1, Jiao Xin1, Lun Fei1, Sun Qiangqiang1, Sun Danfeng12ORCID
Affiliation:
1. College of Land Science and Technology, China Agricultural University, Beijing 100193, China 2. Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture, Beijing 100083, China
Abstract
Accurate inventories of grasslands are important for studies of greenhouse gas (GHG) dynamics, as grasslands store about one-third of the global terrestrial carbon stocks. This paper develops a framework for large-area grassland mapping based on the probability of grassland occurrence and the interactive pathways of fractional vegetation and soil-related endmember nexuses. In this study, grassland occurrence probability maps were produced based on data on bio-climate factors obtained from MODIS/Terra Land Surface Temperature (MOD11A2), MODIS/Terra Vegetation Indices (MOD13A3), and Tropical Rainfall Measuring Mission (TRMM 3B43) using the random forests (RF) method. Time series of 8-day fractional vegetation-related endmembers (green vegetation, non-photosynthetic vegetation, sand land, saline land, and dark surfaces) were generated using linear spectral mixture analysis (LSMA) based on MODIS/Terra Surface Reflectance data (MOD09A1). Time-series endmember fraction maps and grassland occurrence probabilities were employed to map grassland distribution using an RF model. This approach improved the accuracy by 5% compared to using endmember fractions alone. Additionally, based on the grassland occurrence probability maps, we identified extensive ecologically sensitive regions, encompassing 1.54 (104 km2) of desert-to-steppe (D-S) and 2.34 (104 km2) of steppe-to-meadow (S-M) transition regions. Among these, the D-S area is located near the threshold of 310 mm/yr in precipitation, an annual temperature of 10.16 °C, and a surface comprehensive drought index (TVPDI) of 0.59. The S-M area is situated close to the line of 437 mm/yr in precipitation, an annual temperature of 5.49 °C, and a TVPDI of 0.83.
Funder
National Natural Science Foundation of China
Subject
General Earth and Planetary Sciences
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