Unraveling land use land cover change, their driving factors, and implication on carbon storage through an integrated modelling approach DOI Creative Commons
Ogi Setiawan, Anita Apriliani Dwi Rahayu, Gipi Samawandana

et al.

The Egyptian Journal of Remote Sensing and Space Science, Journal Year: 2024, Volume and Issue: 27(4), P. 615 - 627

Published: Aug. 13, 2024

Land Use Cover (LULC) change is a complex phenomenon driven by various natural and anthropogenic factors, significantly impacting carbon storage potential. By applying integrated models of ANN-CA Markov, GeoDetector, InVEST model, this study aimed to analyze LULC change, their driving implications on in the Forest Management Unit (FMU) Ampang Plampang West Nusa Tenggara, Indonesia. Several data sources were utilized modelling approach, including DEM (Digital Elevation Model), topographical map, Landsat imageries (2011, 2016, 2021), measured density (above ground, below soil, dead organic), socio-economic (number populations, farmer, agricultural land). The dryland forest area constitutes most extensive that has experienced significant declines due deforestation, predominantly transforming into land, these are predicted continue until 2031 with different magnitudes. factors elevation, population pressure distance from settlement. also greatly influenced decline historically (2011–2016) projected (2026–2031). conversion forested areas non-forest LULCs released emissions about 1.89 Mt CO2-eq. findings implied integration been helpful for comprehending complicated interactions among dynamics. results contribute scientific knowledge base land management decision-making policy formulation. Effective changes through low development suggested mitigate loss capacities, foster sustainable goals (SDGs), support Nationally Determined Contribution (NDC), improve ecosystem resilience.

Language: Английский

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects DOI Open Access
Lei Tian,

Xiaocan Wu,

Tao Yu

et al.

Forests, Journal Year: 2023, Volume and Issue: 14(6), P. 1086 - 1086

Published: May 24, 2023

Quantifying forest aboveground biomass (AGB) is essential for elucidating the global carbon cycle and response of ecosystems to climate change. Over past five decades, remote-sensing techniques have played a vital role in AGB estimation at different scales. Here, we present an overview progress remote sensing-based estimation. More detail, first describe principles sensing estimation: that is, construction use parameters associated with (rather than direct measurement values). Second, review remotely sensed data sources (including passive optical, microwave, LiDAR) methods (e.g., empirical, physical, mechanistic, comprehensive models) alongside their limitations advantages. Third, discuss possible uncertainty resultant estimates, including those imagery, sample plot survey data, stand structure, statistical models. Finally, offer forward-looking perspectives insights on prospective research directions Remote anticipated play increasingly important future studies. Overall, this may (1) benefit communities focused cycle, sensing, change elucidation, (2) provide theoretical basis study change, (3) inform management, (4) aid elucidation feedbacks

Language: Английский

Citations

75
Scenario simulation of land use change and carbon storage response in Henan Province, China: 1990–2050 DOI Creative Commons

Liyao Fan,

Tianyi Cai, Qian Wen

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 154, P. 110660 - 110660

Published: July 15, 2023

The carbon storage service of terrestrial ecosystems has an veritable impact on the global cycle and, in turn, climate change. Hence, both assessing and predicting land use changes are necessary to reduce emissions mitigate Therefore, using integrated valuation ecosystem services tradeoffs (InVEST) model with remote sensing data, this study systematically analyzes use/cover change (LUCC) response characteristics types Henan Province, China 1990–2020 period. also uses patch-generating simulation (PLUS) predict LUCC Province from 2023 2050 under different scenarios, including Business as Usual (BAU), Ecological Conservation (EC), Urban Development (UD) scenarios. following results noted: (1) mainly comprises conversion farmland construction land. Presently, Province's is found have decreased by 339.72 Tg due LUCC, which characterized "high west low east." (2) Regarding three aforementioned province's predicted increase its greatest extent UD scenario. Under EC scenario, woodland areas will be effectively protected. highest level reserves likely followed that BAU while lowest should seen 312.07 Tg, 233.43 394.49 lower than 2020 BAU, EC, respectively. In sum, provides scientific basis decisions aimed at facilitation low-carbon development, optimal utilization spaces, development ecological civilization Province.

Language: Английский

Citations

52
Land-use carbon emissions and built environment characteristics: A city-level quantitative analysis in emerging economies DOI
Yifu Ou, Zhikang Bao, S. Thomas Ng

et al.

Land Use Policy, Journal Year: 2023, Volume and Issue: 137, P. 107019 - 107019

Published: Dec. 9, 2023

Language: Английский

Citations

48
Effects of land use/cover change on carbon storage between 2000 and 2040 in the Yellow River Basin, China DOI Creative Commons

Chenglong Xu,

Qi‐Bin Zhang, Qiang Yu

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 151, P. 110345 - 110345

Published: May 11, 2023

Land use/cover change (LUCC) is the primary source of carbon storage changes in ecosystem. Up to now, there are few studies about impacts and driving mechanisms LUCC for ecosystem at spatial–temporal scales. Characterizing Yellow River Basin (YRB) its role very important necessary elucidate results human activities on ecosystems. The policies address potential future risks should be formulated advance achieve effective development. In paper, we regarded YRB as study area, analyzed during 2000 2020, predicted land use patterns 2040 under scenarios natural trend (NT), ecological degradation (ED), restoration (ER) using Markov model with Patch-generating Use Simulation (PLUS) model, quantified ecosystems over last 20 years according Integrated Valuation Ecosystem Services Tradeoffs (InVEST) model. outcome was follows: (1) During 2040, changed markedly, cropland being transformed into woodland, grassland built-up land; (2) an upward a mean annual increase 1.93×106Mg C, woodland answer increasing storage, while unused could induce decrease; (3) Carbon varied different degrees three scenarios, but premise not causing large-scale damage, conversion means improving greatly enhancing sequestration efficiency capacity YRB. conclusion, environmental management continuously oriented protection low-carbon development, so that basin will able develop benign direction.

Language: Английский

Citations

44
Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River Basin (1992–2050) DOI
Haoyang Wang,

Lishu Wu,

Yongsheng Yue

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 930, P. 172557 - 172557

Published: April 20, 2024

Language: Английский

Citations

20
Optimizing the Land Use and Land Cover Pattern to Increase Its Contribution to Carbon Neutrality DOI Creative Commons
Kai Wang, Xiaobing Li,

Xin Lyu

et al.

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(19), P. 4751 - 4751

Published: Sept. 23, 2022

Land use and land cover (LULC) contribute to both carbon storage emissions. Therefore, regulating the LULC is an important means of achieving neutrality under global environmental change. Here, West Liaohe River Basin, a semiarid watershed, was taken as case study. Based on assessment emissions induced by from 2000–2020, we set up three different coupled shared socioeconomic pathway (SSP) representative concentration (RCP) scenarios (SSP119, SSP245, SSP585), 2030–2060, optimize LULC. Then, patterns each scenario were simulated using patch-generating simulation (PLUS) model, corresponding changes in compared analyzed. It found that, since 2000, with expansion forest, cropland, construction land, well degradation grassland, have significantly increased, but increase lower than that The simulations revealed when LULC, mainly including protection ecological such forest grassland western southern edges basin, control management cropland northeast central parts there will be significant reduction 2030–2060. This indicates zone-based measures rational regulation can achievement study area. Supported results this study, direct decision-making basis for policy promote regional sustainable development undertaken basin. also provides reference low-carbon other regions.

Language: Английский

Citations

45
Urban flood risk differentiation under land use scenario simulation DOI Creative Commons
Hongbo Zhao,

Tianshun Gu,

Junqing Tang

et al.

iScience, Journal Year: 2023, Volume and Issue: 26(4), P. 106479 - 106479

Published: March 23, 2023

The frequent urban floods have seriously affected the regional sustainable development in recent years. It is significant to understand characteristics of flood risk and reasonably predict under different land use scenarios. This study used random forest multi-criteria decision analysis models assess spatiotemporal Zhengzhou City, China, from 2005 2020, proposed a robust method coupling Bayesian network patch-generating simulation future probability. We found that City presented an upward trend its spatial pattern was "high middle low surrounding areas". In addition, patterns scenario would be more conducive reducing risk. Our results can provide theoretical support for scientifically optimizing improve management.

Language: Английский

Citations

35
Spatiotemporal Evolution and Multi-Scenario Prediction of Carbon Storage in the GBA Based on PLUS–InVEST Models DOI Open Access

Ruei-Yuan Wang,

Huina Cai,

Lingkang Chen

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(10), P. 8421 - 8421

Published: May 22, 2023

In the context of sustainable development and dual-carbon construction, in order to clarify future changes land use carbon storage GBA, this study used PLUS InVEST models as well Geoda software simulate predict spatial pattern stocks GBA 2030 under multiple scenarios. The results show that (1) From 1990 2020, decreased year by year. (2) 2030, except for EPS, prediction values remaining scenarios are lower than those especially value EDS, which is lowest at 8.65 × 108 t. (3) distribution has significant heterogeneity. high-value areas distributed east west wings southwest while low-value concentrated middle east. research can provide a reasonable scientific basis territorial space resource planning goal “dual carbon”.

Language: Английский

Citations

25
Spatiotemporal trends in ecosystem carbon stock evolution and quantitative attribution in a karst watershed in southwest China DOI Creative Commons
Yue Li,

Huacai Geng

Ecological Indicators, Journal Year: 2023, Volume and Issue: 153, P. 110429 - 110429

Published: June 1, 2023

Karst ecosystems serve as a vital part of the Earth's ecosystem and have substantial influence on worldwide carbon cycle. Revealing features driving factors spatiotemporal evolution Carbon (C) stock in karst watersheds is critical for in-depth exploration regional cycle sources/sinks, well ecological restoration. In this study, Nanming River Basin, representative basin southwest China, was used subject region. Based upon data land use change from 2000 to 2020, an Integrated Valuation Ecosystem Services & Tradeoffs (InVEST) model applied calculate C 2020 identify using optimal parameters-based geographical detector (OPGD) model. The findings indicate that: (1) cumulative reduction 3.16 × 105 t; center gravity increase has shifted by 2434.16 m, 7260.53 m. (2) transition forest into construction had highest contribution decrease (60.91%); cultivated grassland conducive rise stock, these conversions contributed 45.93% 35.00%, respectively, stock. (3) normalized difference vegetation index (NDVI), population density, intensity human activity, slope, lithology all annual average q-values greater than 10%, meaning they are primary spatial differentiation NDVI ∩ slope direction heterogeneity largest among interactive factors, with explanatory power close 30%. combinations drivers showed nonlinear enhancement or two-factor effects. To some extent, study deepens changes related mechanisms areas, intending provide scientific foundation recovery fragile support low-carbon economy.

Language: Английский

Citations

23
Ecosystem services response to future land use/cover change (LUCC) under multiple scenarios: A case study of the Beijing-Tianjin-Hebei (BTH) region, China DOI
Wenbo Xu,

XU Heng-zhou,

Xiaoyan Li

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 205, P. 123525 - 123525

Published: June 15, 2024

Language: Английский

Citations

11