Near and far future conservation, land use, and land cover interactions around the wider Etosha landscape, north-central Namibia DOI Creative Commons
Rebecca Kariuki, Jessica Thorn,

John K. E. Mfune

и другие.

Regional Environmental Change, Год журнала: 2025, Номер 25(2)

Опубликована: Апрель 28, 2025

Язык: Английский

Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual analysis DOI
Faisal Mumtaz, Jing Li, Qinhuo Liu

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 905, С. 166940 - 166940

Опубликована: Сен. 9, 2023

Язык: Английский

Процитировано

17
Linking hydrological connectivity to sustainable watershed management in the Loess Plateau of China DOI
Yang Yu,

Juanlong Feng,

Hu Liu

и другие.

Current Opinion in Environmental Science & Health, Год журнала: 2023, Номер 35, С. 100493 - 100493

Опубликована: Июль 13, 2023

Язык: Английский

Процитировано

13
Investigating Land Cover Changes and Their Impact on Land Surface Temperature in Khyber Pakhtunkhwa, Pakistan DOI Open Access

Hammad Ul Hussan,

Hua Li, Qinhuo Liu

и другие.

Sustainability, Год журнала: 2024, Номер 16(7), С. 2775 - 2775

Опубликована: Март 27, 2024

Restoration of degraded land is a significant concern in the 21st century order to combat impacts climate change. For this reason, provisional government Khyber Pakhtunkhwa (KPK), Pakistan, initialized Billion Tree Tsunami Project (BTTP) 2013 and finished it 2017. Although few researchers have investigated use transitions under BTTP short term by merging all vegetation types into one, analysis long-term benefits project future persistence were missing. Furthermore, previous studies not discussed whether prime objective was achieved. Considering existing gaps, research mainly involves analyzing (i) fluctuations green fraction employing change modeler (LCM), along with spatial location gain-loss exchange using high-resolution dataset (GLC30); (ii) forest cover changes influence BTTP; (iii) towards surface temperature (LST) utilizing less-explored technique curve fit linear regression modeling (CFLR); finally, (iv) assessing NDVI LST trends Hurst exponent. Research findings indicate that as an output BTTP, despite government’s claim increasing 2%, gain grassland (3904.87 km2) observed at cost bare land. In comparison, overall increase only 0.39%, which does satisfy main project. On other hand, CFLRM-based actual contributions (LCC) transition decline areas gains for both forest. At same time, reverse transitions. results appear positive climatic term, HURST model-based revealed locations decreasing fall weakly persistent category, therefore these may continue near future. Despite some impact on attributed increase, cannot be regarded complete success due its failure achieve objective.

Язык: Английский

Процитировано

4
Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index DOI
Tao Qi, Qiang Ren, Chunyang He

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 928, С. 172481 - 172481

Опубликована: Апрель 16, 2024

Язык: Английский

Процитировано

4
Effect of land use and land cover changes on land surface warming in an intensive agricultural region DOI
Jesús Gabriel Rangel‐Peraza, Antonio J. Sanhouse-García,

Lizbeth M Flores-González

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 371, С. 123249 - 123249

Опубликована: Ноя. 15, 2024

Язык: Английский

Процитировано

4
NDVI-based spatial and temporal vegetation trends and their response to precipitation and temperature changes in the Mu Us Desert from 2000 to 2019 DOI Creative Commons

Lei Shi,

Hongjian Fan,

Liangyan Yang

и другие.

Water Science & Technology, Год журнала: 2023, Номер 88(2), С. 430 - 442

Опубликована: Июль 4, 2023

This paper explores the relationship between normalized vegetation index (NDVI) response to precipitation and temperature conditions by analyzing spatial temporal variation of cover in Mu Us Desert during 2000-2019. MODIS indices are designed provide consistent comparisons conditions. Maximum Value Composites (MVC) is an internationally used statistical method for NDVI data. Based on remote sensing data, sandy land from 2000 2019 was analyzed using linear regression slope method. In 2000-2010 2010-2019, there a difference change rate Desert, with average 0.0650/10a former 0.0782/10a latter. The trends values study area 2000-2019 were roughly same as those precipitation, slightly different temperature, but overall correlation both good. There significant positive annual (0.687), weak (0.264). growth affected temperature.

Язык: Английский

Процитировано

9
Machine Learning for Modeling Soil Organic Carbon as Affected by Land Cover Change in the Nebraska Sandhills, USA DOI
Lidong Li, Wanwan Liang, Tala Awada

и другие.

Environmental Modeling & Assessment, Год журнала: 2024, Номер 29(3), С. 535 - 547

Опубликована: Апрель 1, 2024

Язык: Английский

Процитировано

3
Drought risk assessment on arid region under different socioeconomic scenarios: A case of Loess Plateau, China DOI Creative Commons
Jinjun Guo, Dongyang Xiao, Xialing Sun

и другие.

Ecological Indicators, Год журнала: 2024, Номер 167, С. 112728 - 112728

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

3
Application of Analytical Hierarchical Process and its Variants on Remote Sensing Datasets DOI
Sarthak Arora,

Michael Warner,

Amanda J. Chamberlain

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Indigenous farmers’ knowledge and perception of desertification and soil erosion in Jigawa State, Nigeria DOI Creative Commons

Abdulkadir Gambo,

M. A. Fullen,

Timothy C. Baldwin

и другие.

Discover Soil., Год журнала: 2025, Номер 2(1)

Опубликована: Март 17, 2025

Язык: Английский

Процитировано

0