Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability DOI Creative Commons
Danish Raza, Hong Shu, Muhsan Ehsan

et al.

Cogent Food & Agriculture, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 7, 2025

Accurate insights into the spatial distribution of cultivated areas, land use for effective agricultural management, and improvement food security planning, especially in developing countries. Therefore, this study examined impact changes population growth on wheat crop productivity. First, by incorporating more than three decades satellite data (1990–2022) different Landsat missions with machine learning algorithms, high-confidence classes were defined features, including cropland. Second, grown area was identified using cropland extraction based acreage assessment method (CLE-WAAM). Third, dynamics applying an exponential model to forecast predict demand. These findings necessitate integrated methodological development demand supply mechanisms two-step floating catchment (2SFCA) approach a thorough analysis socioeconomic developments. The results revealed that transformed non-cropland, percentage 8.01. A 79% rise occured between 1990 2022, projected increase 112% 2030. Specifically, cultivation decreased 28%, despite stagnant parameters observed since 2000. proposed contributes efficiently United Nations' sustainable goal (02: Zero Hunger) satellite, geospatial, statistical integration.

Language: Английский

Land surface temperature responses to land use dynamics in urban areas of Doha, Qatar DOI Creative Commons
Shikha Patel, Madhavi Indraganti, Rana N. Jawarneh

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 104, P. 105273 - 105273

Published: Feb. 13, 2024

Rapid urbanization primarily converts naturally vegetated areas and pervious surfaces into impervious built-up areas, significantly transforming microclimates ecological dynamics. The surfaces, marked by their higher thermal conductivity, disrupt surface energy balance accumulate solar heat, subsequently elevating the land temperatures (LSTs). This study investigates impact of use cover changes on summer winter LSTs in Doha Al Dayeen municipalities Qatar, spanning from years 2000 to 2023, using remote sensing techniques Geographic Information Systems (GIS). analysis reveals a remarkable 343.16% increase area at expense previously existing desert lands water bodies. While Qatar's has high temperature, substituting such with exhibits notable rise temperatures. Additionally, reclamation also results elevated LSTs. LST data derived sources demonstrates an upward trend for contrasting winter. Specifically, mean increases 7.64°C (0.34°C annually), decreases 4.87°C (0.22°C annually). Notably, consistently recorded highest both seasons all observed years. A strong correlation was between patterns Normalized Difference Vegetation Index (NDVI), Water (NDWI), Built-up index (NDBI) Barrenness (NDBal). imply negative influence climate change urgent need urban planning mitigation measures counteract adverse effects increasing LSTs, particularly months, ensure human well-being resilience environments.

Language: Английский

Citations

23
Unveiling Fractional Vegetation Cover Dynamics: A Spatiotemporal Analysis Using MODIS NDVI and Machine Learning DOI Creative Commons
Shoaib Ahmad Anees, Kaleem Mehmood,

Akhtar Rehman

et al.

Environmental and Sustainability Indicators, Journal Year: 2024, Volume and Issue: unknown, P. 100485 - 100485

Published: Sept. 1, 2024

Language: Английский

Citations

21
Analytical study on the relationship among land surface temperature, land use/land cover and spectral indices using geospatial techniques DOI Creative Commons
Atul K. Tiwari, Rolee Kanchan

Discover Environment, Journal Year: 2024, Volume and Issue: 2(1)

Published: Jan. 2, 2024

Abstract Monitoring changes in Land Use/Land Cover (LULC), spectral indices, and Surface Temperature (LST) can help to identify the areas at risk for indefensible land use, a low-grade environment, especially urban heat islands (UHI). This study aims examine changing pattern of LULC, dynamics geospatial indices (Normalised Difference Vegetation Index (NDVI), Normalised Built-up (NDBI), Water (NDWI), Bareness (NDBaI), Latent-heat (NDLI)), LST patterns with relationship among them between 1991 2021 Varanasi City Development Region (VCDR). The LULC classification was done into seven classes (using maximum likelihood method), has been retrieved, above have calculated using Landsat 5 8 data. Pearson’s correlation method used analyse indices. As per result, built-up area increased by 507.8 cent consequently, water bodies, agricultural, barren, fallow vegetation cover were declined 4.84, 18.68, 82.41, 26.18 22.16 respectively during 1991–2021. maximum, minimum, mean 6.18, 2.28, 2.24 °C, respectively, throughout period. A positive observed NDBI, NDBaI, NDLI, LST, whereas NDVI, NDWI, an inverse relationship. finding explains high number healthy cover, sufficient open space, less concrete surface are necessary maintain its related problems. So, SPURS plan proposed thermal environment VCDR. be useful guide planners policymakers providing scientific background as well suggestions sustainable management development VCDR other cities well.

Language: Английский

Citations

20
Assessing forest cover changes and fragmentation in the Himalayan temperate region: implications for forest conservation and management DOI
Kaleem Mehmood, Shoaib Ahmad Anees,

Akhtar Rehman

et al.

Journal of Forestry Research, Journal Year: 2024, Volume and Issue: 35(1)

Published: April 27, 2024

Language: Английский

Citations

20
Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability DOI Creative Commons
Danish Raza, Hong Shu, Muhsan Ehsan

et al.

Cogent Food & Agriculture, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 7, 2025

Accurate insights into the spatial distribution of cultivated areas, land use for effective agricultural management, and improvement food security planning, especially in developing countries. Therefore, this study examined impact changes population growth on wheat crop productivity. First, by incorporating more than three decades satellite data (1990–2022) different Landsat missions with machine learning algorithms, high-confidence classes were defined features, including cropland. Second, grown area was identified using cropland extraction based acreage assessment method (CLE-WAAM). Third, dynamics applying an exponential model to forecast predict demand. These findings necessitate integrated methodological development demand supply mechanisms two-step floating catchment (2SFCA) approach a thorough analysis socioeconomic developments. The results revealed that transformed non-cropland, percentage 8.01. A 79% rise occured between 1990 2022, projected increase 112% 2030. Specifically, cultivation decreased 28%, despite stagnant parameters observed since 2000. proposed contributes efficiently United Nations' sustainable goal (02: Zero Hunger) satellite, geospatial, statistical integration.

Language: Английский

Citations

4