[HTML][HTML] Crop monitoring by multimodal remote sensing: A review

P Karmakar, SW Teng, M Murshed, S Pang, Y Li… - Remote Sensing …, 2024 - Elsevier
Effective approaches to achieve food safety and security can prevent catastrophic situations.
Therefore, it is required to monitor agricultural crops on a regular basis. This can be easily …

[HTML][HTML] Integrating forest cover change and carbon storage dynamics: Leveraging Google Earth Engine and InVEST model to inform conservation in hilly regions

AA Kafy, M Saha, MA Fattah, MT Rahman, BM Duti… - Ecological …, 2023 - Elsevier
Forests are vital in combating climate change by storing and sequestrating CO 2 from the
atmosphere. Measuring the influence of land use/land cover (LULC) changes on the …

Using machine learning and remote sensing to track land use/land cover changes due to armed conflict

S Mhanna, LJS Halloran, F Zwahlen, AH Asaad… - Science of The Total …, 2023 - Elsevier
Armed conflicts have detrimental impacts on the environment, including land systems. The
prevailing understanding of the relation between Land Use/Land Cover (LULC) and armed …

[HTML][HTML] Evaluating the ecological security of ecotourism in protected area based on the DPSIR model

P Sobhani, H Esmaeilzadeh, ID Wolf, A Deljouei… - Ecological …, 2023 - Elsevier
Evaluating the ecological security of ecotourism (EES) in protected areas is critical because
these areas play a vital role in protecting biodiversity and natural resources. This study …

Spatial–temporal and driving factors of land use/cover change in Mongolia from 1990 to 2021

J Hao, Q Lin, T Wu, J Chen, W Li, X Wu, G Hu, Y La - Remote Sensing, 2023 - mdpi.com
During the past several decades, desertification and land degradation have become more
and more serious in Mongolia. The drivers of land use/cover change (LUCC), such as …

Modeling wildfire risk in western Iran based on the integration of AHP and GIS

V Nasiri, SMM Sadeghi, R Bagherabadi… - Environmental …, 2022 - Springer
This study aimed at delineating the wildfire risk zones in a fire-prone region located in a
rarely addressed area of western Iran (Paveh city) by assessing the potential of factors such …

Improving forest detection using machine learning and remote sensing: A Case study in Southeastern Serbia

I Potić, Z Srdić, B Vakanjac, S Bakrač, D Đorđević… - Applied Sciences, 2023 - mdpi.com
Featured Application The primary application of this work is in environmental resource
management, specifically in the detection and monitoring of vegetation patterns and …

Using Landsat-5 for accurate historical LULC classification: A comparison of machine learning models

D Krivoguz, SG Chernyi, E Zinchenko, A Silkin… - Data, 2023 - mdpi.com
This study investigates the application of various machine learning models for land use and
land cover (LULC) classification in the Kerch Peninsula. The study utilizes archival field …

Deep learning in the mapping of agricultural land use using Sentinel-2 satellite data

G Singh, S Singh, G Sethi, V Sood - Geographies, 2022 - mdpi.com
Continuous observation and management of agriculture are essential to estimate crop yield
and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to …

Machine learning based combinatorial analysis for land use and land cover assessment in Kyiv City (Ukraine)

V Belenok, L Hebryn-Baidy… - Journal of Applied …, 2023 - spiedigitallibrary.org
The main goal of this study is to evaluate different models for further improvement of the
accuracy of land use and land cover (LULC) classification on Google Earth Engine using …