Improving Fmask cloud and cloud shadow detection in mountainous area for Landsats 4–8 images
We developed a new algorithm called MFmask (Mountainous Fmask) for automated cloud
and cloud shadow detection for Landsats 4–8 images acquired in mountainous areas. The …
and cloud shadow detection for Landsats 4–8 images acquired in mountainous areas. The …
A cloud-based multi-temporal ensemble classifier to map smallholder farming systems
Smallholder farmers cultivate more than 80% of the cropland area available in Africa. The
intrinsic characteristics of such farms include complex crop-planting patterns, and small …
intrinsic characteristics of such farms include complex crop-planting patterns, and small …
Detecting and monitoring long-term landslides in urbanized areas with nighttime light data and multi-seasonal Landsat imagery across Taiwan from 1998 to 2017
Monitoring long-term landslide activity is of importance for risk assessment and land
management. Daytime airborne drones or very high-resolution optical satellites are often …
management. Daytime airborne drones or very high-resolution optical satellites are often …
In-season crop mapping with GF-1/WFV data by combining object-based image analysis and random forest
Producing accurate crop maps during the current growing season is essential for effective
agricultural monitoring. Substantial efforts have been made to study regional crop …
agricultural monitoring. Substantial efforts have been made to study regional crop …
Integration of Sentinel optical and radar data for mapping smallholder coffee production systems in Vietnam
Perennial commodity crops, such as coffee, often play a large role globally in agricultural
markets and supply chains and locally in livelihoods, poverty reduction, and biodiversity …
markets and supply chains and locally in livelihoods, poverty reduction, and biodiversity …
Semantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural network
E Saralioglu, O Gungor - Geocarto International, 2022 - Taylor & Francis
Research to improve the accuracy of very high-resolution satellite image classification
algorithms is still one of the hot topics in the field of remote sensing. Successful results of …
algorithms is still one of the hot topics in the field of remote sensing. Successful results of …
Using Google Earth engine to map complex shade-grown coffee landscapes in Northern Nicaragua
Shade-grown coffee (shade coffee) is an important component of the forested tropics, and is
essential to the conservation of forest-dependent biodiversity. Despite its importance, shade …
essential to the conservation of forest-dependent biodiversity. Despite its importance, shade …
Forest tree species distribution for Europe 2000–2020: mapping potential and realized distributions using spatiotemporal machine learning
This article describes a data-driven framework based on spatiotemporal machine learning to
produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill …
produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill …
Mapping the distribution of coffee plantations from multi-resolution, multi-temporal, and multi-sensor data using a random forest algorithm
Indonesia is the world's fourth largest coffee producer. Coffee plantations cover 1.2 million
ha of the country with a production of 500 kg/ha. However, information regarding the …
ha of the country with a production of 500 kg/ha. However, information regarding the …
An improved algorithm for identifying shallow and deep-seated landslides in dense tropical forest from airborne laser scanning data
Landslides are natural disasters that cause environmental and infrastructure damage
worldwide. They are difficult to be recognized, particularly in densely vegetated regions of …
worldwide. They are difficult to be recognized, particularly in densely vegetated regions of …