151 related articles for article (PubMed ID: 37809681)
21. Impact assessment of urban development patterns on land surface temperature by using remote sensing techniques: a case study of Lahore, Faisalabad and Multan district.
Saleem MS; Ahmad SR; Shafiq-Ur-Rehman ; Javed MA
Environ Sci Pollut Res Int; 2020 Nov; 27(32):39865-39878. PubMed ID: 32748362
[TBL] [Abstract][Full Text] [Related]
22. Drought evolution indicated by meteorological and remote-sensing drought indices under different land cover types in China.
Javed T; Yao N; Chen X; Suon S; Li Y
Environ Sci Pollut Res Int; 2020 Feb; 27(4):4258-4274. PubMed ID: 31828700
[TBL] [Abstract][Full Text] [Related]
23. Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data.
Fallati L; Savini A; Sterlacchini S; Galli P
Environ Monit Assess; 2017 Aug; 189(8):417. PubMed ID: 28748428
[TBL] [Abstract][Full Text] [Related]
24. Assessment of changes in environmental factors in a tourism-oriented Island.
Shi Z; Jiang Y; Zhai X; Zhang Y; Xiao X; Xia J
Front Public Health; 2022; 10():1090497. PubMed ID: 36699879
[TBL] [Abstract][Full Text] [Related]
25. Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India.
Abijith D; Saravanan S
Environ Sci Pollut Res Int; 2022 Dec; 29(57):86055-86067. PubMed ID: 34510357
[TBL] [Abstract][Full Text] [Related]
26. Exploring geospatial techniques for spatiotemporal change detection in land cover dynamics along Soan River, Pakistan.
Bashir H; Ahmad SS
Environ Monit Assess; 2017 May; 189(5):222. PubMed ID: 28429250
[TBL] [Abstract][Full Text] [Related]
27. Bridging the national data gap with Google earth engine and landsat imagery by developing annual land cover for Afghanistan.
Uddin K; Atal SB; Maharjan S; Bajracharya B; Yousafi W; Mayer T; Matin MA; Shakya B; Saah D; Potapov P; Thapa RB; Shakya B
Data Brief; 2024 Jun; 54():110316. PubMed ID: 38550239
[TBL] [Abstract][Full Text] [Related]
28. The spatiotemporal change of cropland and its impact on vegetation dynamics in the farming-pastoral ecotone of northern China.
Wuyun D; Sun L; Chen Z; Hou A; Crusiol LGT; Yu L; Chen R; Sun Z
Sci Total Environ; 2022 Jan; 805():150286. PubMed ID: 34537692
[TBL] [Abstract][Full Text] [Related]
29. Land use/land cover change and land surface temperature of Ibadan and environs, Nigeria.
Fashae OA; Adagbasa EG; Olusola AO; Obateru RO
Environ Monit Assess; 2020 Jan; 192(2):109. PubMed ID: 31932977
[TBL] [Abstract][Full Text] [Related]
30. Land Use and Land Cover Change Detection Using the Random Forest Approach: The Case of The Upper Blue Nile River Basin, Ethiopia.
Tikuye BG; Rusnak M; Manjunatha BR; Jose J
Glob Chall; 2023 Oct; 7(10):2300155. PubMed ID: 37829681
[TBL] [Abstract][Full Text] [Related]
31. Research on the spatial temporary evolution of urban expansion in Xining city and its surrounding areas based on Landsat time series data.
Cao X; Gao X; Li R
Heliyon; 2024 Feb; 10(3):e24846. PubMed ID: 38322889
[TBL] [Abstract][Full Text] [Related]
32. Analysis of forty years long changes in coastal land use and land cover of the Yellow Sea: The gains or losses in ecosystem services.
Yim J; Kwon BO; Nam J; Hwang JH; Choi K; Khim JS
Environ Pollut; 2018 Oct; 241():74-84. PubMed ID: 29803027
[TBL] [Abstract][Full Text] [Related]
33. Accurate classification of land use and land cover using a boundary-specific two-level learning approach augmented with auxiliary features in Google Earth Engine.
Selvaraj R; Amali D GB
Environ Monit Assess; 2023 Oct; 195(11):1280. PubMed ID: 37804363
[TBL] [Abstract][Full Text] [Related]
34. Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis.
Gandharum L; Hartono DM; Karsidi A; Ahmad M
ScientificWorldJournal; 2022; 2022():3123788. PubMed ID: 35069036
[TBL] [Abstract][Full Text] [Related]
35. Research on the spatiotemporal coupling relationships between land use/land cover compositions or patterns and the surface urban heat island effect.
Ma X; Peng S
Environ Sci Pollut Res Int; 2022 Jun; 29(26):39723-39742. PubMed ID: 35107726
[TBL] [Abstract][Full Text] [Related]
36. Dynamics changes of coastal aquaculture ponds based on the Google Earth Engine in Jiangsu Province, China.
Li X; Zhao P; Liang M; Ji X; Zhang D; Xie Z
Mar Pollut Bull; 2024 Jun; 203():116502. PubMed ID: 38776642
[TBL] [Abstract][Full Text] [Related]
37. Modelling of land use land cover changes using machine learning and GIS techniques: a case study in El-Fayoum Governorate, Egypt.
Atef I; Ahmed W; Abdel-Maguid RH
Environ Monit Assess; 2023 May; 195(6):637. PubMed ID: 37133528
[TBL] [Abstract][Full Text] [Related]
38. Studying land use dynamics using decadal satellite images and Dyna-CLUE model in the Mahanadi River basin, India.
Das P; Behera MD; Pal S; Chowdary VM; Behera PR; Singh TP
Environ Monit Assess; 2020 Jan; 191(Suppl 3):804. PubMed ID: 31989334
[TBL] [Abstract][Full Text] [Related]
39. Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine.
Roy B; Bari E
Heliyon; 2022 Sep; 8(9):e10668. PubMed ID: 36164525
[TBL] [Abstract][Full Text] [Related]
40. Geospatial modeling to assess the past and future land use-land cover changes in the Brahmaputra Valley, NE India, for sustainable land resource management.
Debnath J; Sahariah D; Lahon D; Nath N; Chand K; Meraj G; Farooq M; Kumar P; Kanga S; Singh SK
Environ Sci Pollut Res Int; 2023 Oct; 30(49):106997-107020. PubMed ID: 36418825
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]