Framework for near real-time forest inventory using multi source remote sensing data

NC Coops, P Tompalski, TRH Goodbody, A Achim… - Forestry, 2023 - academic.oup.com
Forestry inventory update is a critical component of sustainable forest management,
requiring both the spatially explicit identification of forest cover change and integration of …

Automated attribution of forest disturbance types from remote sensing data: A synthesis

AT Stahl, R Andrus, JA Hicke, AT Hudak… - Remote Sensing of …, 2023 - Elsevier
Remote sensing is widely used to detect forest disturbances (eg, wildfires, harvest, or
outbreaks of pathogens or insects) over spatiotemporal scales that are infeasible to capture …

Crop type and land cover mapping in northern Malawi using the integration of sentinel-1, sentinel-2, and planetscope satellite data

D Kpienbaareh, X Sun, J Wang, I Luginaah… - Remote Sensing, 2021 - mdpi.com
Mapping crop types and land cover in smallholder farming systems in sub-Saharan Africa
remains a challenge due to data costs, high cloud cover, and poor temporal resolution of …

Integrating GEDI and Landsat: Spaceborne lidar and four decades of optical imagery for the analysis of forest disturbances and biomass changes in Italy

S Francini, G D'Amico, E Vangi, C Borghi, G Chirici - Sensors, 2022 - mdpi.com
Forests play a prominent role in the battle against climate change, as they absorb a relevant
part of human carbon emissions. However, precisely because of climate change, forest …

Integration of Sentinel 1 and Sentinel 2 satellite images for crop mapping

S Felegari, A Sharifi, K Moravej, M Amin, A Golchin… - Applied Sciences, 2021 - mdpi.com
Crop identification is key to global food security. Due to the large scale of crop estimation,
the science of remote sensing was able to do well in this field. The purpose of this study is to …

[HTML][HTML] An open science and open data approach for the statistically robust estimation of forest disturbance areas

S Francini, RE McRoberts, G D'Amico… - International Journal of …, 2022 - Elsevier
Forest disturbance monitoring is critical for understanding forest-related greenhouse gas
emissions and for determining the role of forest management in mitigating climate change …

Mapping tropical forest cover and deforestation with Planet NICFI satellite images and deep learning in Mato Grosso State (Brazil) from 2015 to 2021

FH Wagner, R Dalagnol, CHL Silva-Junior, G Carter… - Remote Sensing, 2023 - mdpi.com
Monitoring changes in tree cover for assessment of deforestation is a premise for policies to
reduce carbon emission in the tropics. Here, a U-net deep learning model was used to map …

[HTML][HTML] An assessment approach for pixel-based image composites

S Francini, T Hermosilla, NC Coops, MA Wulder… - ISPRS Journal of …, 2023 - Elsevier
Remote sensing is one of the main sources of information for monitoring forest dynamics;
however, surface reflectance is often not possible to accurately derive due to haze, cloud, or …

Timeliness in forest change monitoring: A new assessment framework demonstrated using Sentinel-1 and a continuous change detection algorithm

EL Bullock, SP Healey, Z Yang, R Houborg… - Remote Sensing of …, 2022 - Elsevier
The development of near-real time forest monitoring systems, which are used to create alerts
for events such as logging or fire, often involves tradeoffs between accuracy and timeliness …

Leveraging past information and machine learning to accelerate land disturbance monitoring

S Ye, Z Zhu, JW Suh - Remote Sensing of Environment, 2024 - Elsevier
Near real-time (NRT) monitoring of land disturbances holds great importance for delivering
emergency aid, mitigating negative social and ecological impacts, and distributing resources …