Land use changes are always patchy and widespread within a region, making it a challenge to identify the point-scale pressure of reducing carbon emissions from land use/cover change (LUCC). The carbon emission observation index (CEOI) was thus proposed to conduct the point-scale comparability analysis, which was based on the unique net C flux effects of conversions between two different land use types. Then, the spatial-temporal characteristics of land use changes and the resulting pressure of reducing carbon emissions were studied in the Weihe River Basin of China, which adopted the LUCC data from 2000 to 2020 and models of the Markov transition matrix (MTM), compound carbon emission coefficients (CEC) of various types of land use changes, and the CEOI-based classification method on point-scale pressure of reducing carbon emissions. The results showed that: ① The net C flux was from 3.551 Tg C (2000-2010) to 7.031 Tg C (2010-2020), and the pressure of reducing carbon emissions from LUCC had been continuously increasing, which was mainly driven by the significant increase in change-spots with the super-strong ability to reduce carbon emissions. ② Due to contributions from change spots with carbon uptake ability, the amount of carbon released to the atmosphere was eliminated by approximately 19.21% over the period 2000-2020 and approximately 37.4% during 2000-2010. ③ Change spots on various pressure levels for reducing carbon emissions were distributed unevenly in the basin, with their gravity points in the previous 10 years (2010-2020) far away from those during 2000-2010. Additionally, the gravity points of change-spots with a strong ability to reduce carbon emissions from conversions of grassland into forestland moved northeastward from Tianshui City to Pingliang City, whereas the gravity points of other change-spots with different abilities to reduce carbon emissions were mostly northwestward to the north-central region with higher elevations from the Middle and Lower Reaches of the Weihe River Basin with low elevations.

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http://dx.doi.org/10.13227/j.hjkx.202309248DOI Listing

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