Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceClassification of images attributes to categorizing of images into various predefined groups. A particular image can be grouped into several diverse classes. Examining and ordering the images manually is a tiresome job particularly when they are abundant and therefore, automating the entire process using image processing and computer vision would be very efficient and useful. In this study, the Classifier and Regression trees (CART) algorithm is used to create a classifier model that classifies a region based on the feature specified. The Google Earth Engine (GEE) platform is utilized to conduct the study. The Tier 1 USGS Landsat 8 surface refle...
Highland Andean ecosystems sustain high levels of floral and faunal biodiversity in areas with diver...
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferat...
Due to the rapid advancements in the remote sensing field, there is an immense amount of data being ...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceCla...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
Regions with high tourism density are very sensitive to human activities. Ensuring sustainability by...
Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatia...
Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatia...
With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella Na...
Satellite image classification is crucial in various applications such as urban planning, environmen...
A fully automatic phenology-based synthesis (PBS) classification algorithm was developed to map land...
The growing human population accelerates alterations in land use and land cover (LULC) over time, pu...
Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wave...
Highland Andean ecosystems sustain high levels of floral and faunal biodiversity in areas with diver...
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferat...
Due to the rapid advancements in the remote sensing field, there is an immense amount of data being ...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceCla...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
International audienceDetailed, accurate and frequent land cover mapping is a prerequisite for sever...
Regions with high tourism density are very sensitive to human activities. Ensuring sustainability by...
Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatia...
Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatia...
With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella Na...
Satellite image classification is crucial in various applications such as urban planning, environmen...
A fully automatic phenology-based synthesis (PBS) classification algorithm was developed to map land...
The growing human population accelerates alterations in land use and land cover (LULC) over time, pu...
Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wave...
Highland Andean ecosystems sustain high levels of floral and faunal biodiversity in areas with diver...
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferat...
Due to the rapid advancements in the remote sensing field, there is an immense amount of data being ...