A systematic review on advancements in remote sensing for assessing and monitoring land use and land cover changes impacts on surface water resources in semi …

MJ Mashala, T Dube, BT Mudereri, KK Ayisi… - Remote Sensing, 2023 - mdpi.com
This study aimed to provide a systematic overview of the progress made in utilizing remote
sensing for assessing the impacts of land use and land cover (LULC) changes on water …

Machine learning classification of mediterranean forest habitats in google earth engine based on seasonal sentinel-2 time-series and input image composition …

S Praticò, F Solano, S Di Fazio, G Modica - Remote sensing, 2021 - mdpi.com
The sustainable management of natural heritage is presently considered a global strategic
issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) …

High-resolution rice mapping based on SNIC segmentation and multi-source remote sensing images

L Yang, L Wang, GA Abubakar, J Huang - Remote Sensing, 2021 - mdpi.com
High-resolution crop mapping is of great significance in agricultural monitoring, precision
agriculture, and providing critical information for crop yield or disaster monitoring …

[HTML][HTML] Monitoring onion crop “cipolla rossa di Tropea Calabria IGP” growth and yield response to varying nitrogen fertilizer application rates using UAV imagery

G Messina, S Pratico, G Badagliacca, S Di Fazio… - Drones, 2021 - mdpi.com
Remote sensing (RS) platforms such as unmanned aerial vehicles (UAVs) represent an
essential source of information in precision agriculture (PA) as they are able to provide …

Using open data to detect the structure and pattern of informal settlements: an outset to support inclusive SDGs' achievement

Z Assarkhaniki, S Sabri, A Rajabifard - Big Earth Data, 2021 - Taylor & Francis
The detection of informal settlements is the first step in planning and upgrading deprived
areas in order to leave no one behind in SDGs. Very High-Resolution satellite images …

Sugarcane crop type discrimination and area mapping at field scale using sentinel images and machine learning methods

A Nihar, NR Patel, S Pokhariyal, A Danodia - Journal of the Indian Society …, 2022 - Springer
Crop mapping and acreage estimation are the simplest yet the most critical issues in
agriculture. Remote sensing technology has been extensively used in the past few decades …

SatRed: New classification land use/land cover model based on multi-spectral satellite images and neural networks applied to a semiarid valley of Patagonia

MA Trujillo-Jiménez, AL Liberoff, N Pessacg… - Remote Sensing …, 2022 - Elsevier
In this article we describe a new model, SatRed, which classifies land use and land cover
(LULC) from Sentinel-2 imagery and data acquired in the field. SatRed performs pixel-level …

Machine-learning algorithms for land use dynamics in Lake Haramaya Watershed, Ethiopia

GW Woldemariam, D Tibebe, TE Mengesha… - Modeling Earth Systems …, 2022 - Springer
Natural and human-induced drivers within the constraints of multiple socioeconomic and
political conditions have intensified the extent of land use and land cover (LULC) change at …

Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images

G Wang, D Meng, R Chen, G Yang, L Wang, H Jin… - Remote Sensing, 2024 - mdpi.com
Timely and accurate rice spatial distribution maps play a vital role in food security and social
stability. Early-season rice mapping is of great significance for yield estimation, crop …

Pixel-based vs. object-based anthropogenic impervious surface detection: driver for urban-rural thermal disparity in Faridabad, Haryana, India

S Kumar, K Midya, S Ghosh, S Singh - Geocarto International, 2022 - Taylor & Francis
Anthropogenic impervious surface area (AISA) expansion with its impact on temperature is
current research trend. Majority of earlier research focused on land surface temperature …