Unveiling grassland dynamics: trends and drivers of degradation and improvement in the Eurasian Steppe since 2000 DOI Creative Commons
Ziyu Yan, Bin Sun,

Zhihai Gao

и другие.

GIScience & Remote Sensing, Год журнала: 2024, Номер 61(1)

Опубликована: Ноя. 21, 2024

As the most extensive temperate grassland in world, Eurasian Steppe provides various ecological services that support environment and human well-being. However, degradation has become a serious environmental issue. Most of traditional assessments ignore sensitivity ecosystems to climatic conditions. In response, our study introduces new comprehensive identification framework integrates vegetation growth climate change, using novel long-term monitoring methodology detect improvement. The quantifies area degree improvement long time-series data from 2000 − 2020. Then, driving factors change were analyzed quantitative model. Our findings reveal clear trend was identified, with improved being 4.72 times larger than degraded (221.4 × 104 46.92 km2, respectively). Tibetan Plateau Loess led Simultaneously, surrounding northern Caspian Sea been severely degraded. three areas correspond frigid humid semi-humid grassland, arid semi-arid respectively. Globally, combined effects activities dominated observed improvement, accounting for 77.13% 89.64%, method robust tool detecting across large scales, offering scientific achieving United Nations' Sustainable Development Goals (SDGs), particularly land neutrality (LDN).

Язык: Английский

Ecological response of green spaces to land use change in the Mu Us Desert-Loess Plateau transition zone, China, since the twenty-first century DOI
Xuegang Gong, Yunzhi Zhang, Jing Ren

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(4)

Опубликована: Март 19, 2025

Язык: Английский

Процитировано

0
Anthropogenic activities accelerate LULC conversion and only a sustainable development scenario is optimal for agro-pastoral ecotone development DOI Creative Commons
Jing Jin,

Zilong Liao,

Tiejun Liu

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 23, 2025

Despite the ecological and socioeconomic importance of agro-pastoral ecotones, changes in land use cover (LULC) their driving mechanisms are not comprehensively understood. In this study, a systematic framework for LULC assessment covering comprehensive timeframes was constructed Tabu watershed. Results demonstrated that new process began 1998, with significant increase farmland decrease grassland. The dynamic degrees structural variation coefficients indicated intensive frequent LULC. Conversion ratios between grassland exceeded 95%, construction encroached upon Grassland were driven mainly by natural factors based on random forest regression, as well land. influence anthropogenic drivers became significant. Under sustainable development scenario, high fractional vegetation 2034 most significant, area bare decreased, steadily increased, reduction under control. both ecosystem stability can be achieved. This study provides insights into regional dynamics guidance management.

Язык: Английский

Процитировано

0
Does climate change induce desertification in Gujarat? DOI
R. Bhatla, Richa Singh,

Priyanka

и другие.

Environmental Earth Sciences, Год журнала: 2025, Номер 84(12)

Опубликована: Май 26, 2025

Язык: Английский

Процитировано

0
Effects of alpine meadow degradation on the soil physical and chemical properties in Maqu, China DOI Creative Commons

Kecun Zhang,

Jing Pan, Zhishan An

и другие.

Research in Cold and Arid Regions, Год журнала: 2024, Номер unknown

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

3
Predicting Fractional Shrub Cover in Heterogeneous Mediterranean Landscapes Using Machine Learning and Sentinel-2 Imagery DOI Open Access
El Khalil Cherif,

R. E. Lucas,

Taha Ait Tchakoucht

и другие.

Forests, Год журнала: 2024, Номер 15(10), С. 1739 - 1739

Опубликована: Окт. 1, 2024

Wildfires pose a growing threat to Mediterranean ecosystems. This study employs advanced classification techniques for shrub fractional cover mapping from satellite imagery in fire-prone landscape Quinta da França (QF), Portugal. The area is characterized by fine-grained heterogeneous land and climate. In this type of landscape, encroachment after abandonment wildfires constitutes ecosystem resilience—in particular, increasing the susceptibility more frequent large fires. High-resolution is, therefore, an important contribution management fire prevention. Here, 20 cm resolution map was used label 10 m Sentinel-2 pixels according their percentage (three categories: 0%, >0%–50%, >50%) training testing. Three distinct algorithms, namely Support Vector Machine (SVM), Artificial Neural Networks (ANNs), Random Forest (RF), were tested purpose. RF excelled, achieving highest precision (82%–88%), recall (77%–92%), F1 score (83%–88%) across all categories (test validation sets) compared SVM ANN, demonstrating its superior ability accurately predict cover. Analysis confusion matrices revealed RF’s (higher true positives) with fewer misclassifications (lower false positives negatives). McNemar’s test indicated statistically significant differences (p value < 0.05) between models, consolidating dominance. development maps derived products anticipated leverage key information support management, such as assessment hazard effective planning preventive actions.

Язык: Английский

Процитировано

2
Achieving land degradation neutrality: land-use planning and ecosystem approach DOI Creative Commons
Pavlo Saik, Іryna Kоshkalda,

Liudmyla Bezuhla

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Окт. 29, 2024

Introduction The research purpose is to scientifically substantiate an integrated approach solving the problem of land degradation, based on idea degradation neutrality (LDN), taking into account ecosystem services when planning use maximize conservation natural capital. methodological basis provisions and principles concepts sustainable development, achieving LDN, services, as well results revealing various aspects use, particularly their degradation. Methods following methods are used in paper: dialectical – determine cause-and-effect conditions degradation; analysis highlight current state Ukraine factors that have led synthesis for global trends towards LDN; deduction explore possibility introducing experience LDN Ukraine; structural-functional feasibility land-use achieve LDN. Results As a result research, has been analyzed, ways through prism substantiated. Based statistical data, potential levels arability territory calculated by natural-climatic zones, areas eroded arable lands determined erodibility factor (low-eroded, mediumeroded,and highly-eroded). Discussion For first time, structural-logical scheme developed organizational-economic support effective degraded low-productive agricultural context implementing which tool rational allocation lands. This can serve development strategies territorial communities, institutions, organizations competent field management.

Язык: Английский

Процитировано

2
Challenges for sustainable development goal of land degradation neutrality in drylands: Evidence from the Northern Slope of the Tianshan Mountains, China DOI
Haochen Yu, Dengyu Yin, Bin Yang

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 932, С. 173094 - 173094

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

1
Spatio-Temporal Land-Use/Cover Change Dynamics Using Spatiotemporal Data Fusion Model and Google Earth Engine in Jilin Province, China DOI Creative Commons

Zhuxin Liu,

Yang Han, Ruifei Zhu

и другие.

Land, Год журнала: 2024, Номер 13(7), С. 924 - 924

Опубликована: Июнь 25, 2024

Jilin Province is located in the northeast of China, and has fragile ecosystems, a vulnerable environment. Large-scale, long time series, high-precision land-use/cover change (LU/CC) data are important for spatial planning environmental protection areas with high surface heterogeneity. In this paper, based on temporal fusion Landsat MODIS Google Earth Engine (GEE), series LU/CC mapping spatio-temporal analysis period 2000–2023 were realized using random forest remote sensing image classification method, which integrates indices. The prediction results OL-STARFM method very close to real images better contained information, allowing its application subsequent classification. average overall accuracy kappa coefficient products obtained fused index 95.11% 0.9394, respectively. During study period, area cultivated land unused decreased as whole. grassland, forest, water fluctuated, while building increased 13,442.27 km2 2023. terms transfer, was most source transfers, total share from 42.98% 38.39%. Cultivated mainly transferred land, transfer 7682.48 km2, 8374.11 7244.52 Grassland largest into among other feature types relatively small, at less than 3300 km2. This provides support scientific management resources Province, resulting dataset great significance regional sustainable development.

Язык: Английский

Процитировано

1
Boundary migration between zonal vegetation types in Inner Mongolia over the past two decades DOI
Haoxin Li, Jingpeng Guo,

Yadong Wang

и другие.

CATENA, Год журнала: 2024, Номер 246, С. 108354 - 108354

Опубликована: Сен. 6, 2024

Язык: Английский

Процитировано

1
A 20-Year Analysis of the Dynamics and Driving Factors of Grassland Desertification in Xilingol, China DOI Creative Commons
Jingbo Li, Chunxiang Cao, Min Xu

и другие.

Remote Sensing, Год журнала: 2023, Номер 15(24), С. 5716 - 5716

Опубликована: Дек. 13, 2023

Grassland desertification stands as an ecological concern globally. It is crucial for prevention and control to comprehend the variation in area severity of desertified grassland (DGL), clarify intensities conversion among DGLs different levels, explore spatial temporal driving factors desertification. In this study, a Desertification Difference Index (DDI) model was constructed based on albedo-EVI extract information. Subsequently, intensity analysis, Geo-detector model, correlation analysis were applied analyze dynamics The results showed following: (1) Spatially, DGL Xilingol exhibited zonal distribution. Temporally, degree decreased, with proportion severely moderately areas decreasing from 51.77% 2000 37.23% 2020, while nondesertified healthy increased 17.85% 37.40% 2020; (2) Transition levels more intense during 2000–2012, stabilizing 2012–2020; (3) Meteorological soil conditions primarily drive distribution DDI, evapotranspiration exhibiting most significant influence (q-value 0.83), human activities dominate interannual DDI variations. This study provides insights into patterns divergent forces shaping both dimensions Xilingol.

Язык: Английский

Процитировано

2