Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach-Reference-Cited by-同舟云学术

Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach

Published:2024-05-04 Issue: Volume: Page:1-28
ISSN:1947-5683
Container-title:Annals of GIS
language:en
Short-container-title:Annals of GIS

Author:

Hussain Khadim¹,Mehmood Kaleem²³,Yujun Sun¹,Badshah Tariq¹,Anees Shoaib Ahmad⁴⁵,Shahzad Fahad⁴⁶,Nooruddin ⁷,Ali Jamshid²,Bilal Muhammad²

Affiliation:

1. State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, P. R. China

2. Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, P. R. China

3. Institute of Agriculture Sciences and Forestry, University of Swat, Swat, Pakistan

4. Beijing Key Laboratory of Precision Forestry, Forestry College, Beijing Forestry University, Beijing, P. R. China

5. Department of Forestry, The University of Agriculture, Dera Ismail Khan, 29050, Pakistan

6. Mapping and 3S Technology Center, Beijing Forestry University, Beijing, China

7. Parks & Wildlife Department, Range Forest Officer Forest, Gilgit Baltistan, Pakistan

Funder

the original work conducted as part of my Ph.D. dissertation, generously supported by the State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475683.2024.2343399

Reference132 articles.

1. Impact assessment of socioeconomic factors on dimensions of environmental degradation in Pakistan

2. An overview of land degradation, desertification and sustainable land management using GIS and remote sensing applications

3. Employing Neural Networks Algorithm for LULC Mapping

4. Geospatial Assessment of Forest Fragmentation and its Implications for Ecological Processes in Tropical Forests

5. The effects of polynomial interpolation and resampling methods in geometric correction on the land-cover classification accuracy of Landsat-8 OLI imagery: a case study of Kulon Progo area, Yogyakarta

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