Soil, due to agricultural and mining activities, can pose significant threats from heavy metal contamination, impacting both environmental health and agricultural productivity. Detecting the severity of soil contamination is crucial. Traditional ground-based methods involve designing regular soil sampling strategies with a measurement depth of 0-5 cm, followed by chemical analysis […]
Remote Sensing
27 posts
The early part of the twenty-first century has recorded the forest carbon loss increasing in the tropical regions. A remote sensing study to this effect was conducted that extensively used the vast collection of Landsat satellite images. Forest cover change Landsat 30 m spatial resolution data was aggregated yearly to […]
Kolleru Lake is India’s largest freshwater lake. In recent years, satellite images of the lake witnessed the fishpond lakes developing, drastically altering the region’s land use and land cover. The analysis employed Landsat images over the year 2018. A median image was generated using all the cloud-free images available during […]
As derived from Landsat series datasets, the satellite-based land surface temperature data is prevalent among researchers studying surface urban heat islands. Surface urban heat island is the term given to the land surface temperature difference in urban areas concerning the land surface temperature of the surrounding surface. The following are […]
The temporal resolution of the remotely sensed images is improving. Therefore, more attention is sought for the change detection applications. The approach of deep learning is being tried on remote sensing datasets. Here are a few supervised deep learning approaches that are applied for change detection applications using multispectral remote […]
Dust storms are one of the climatological phenomena. These events are important because they represent a massive amount of erosion and leave a considerable amount of deposition. Dust storms usually transport silt-sized material from the world’s deserts to distant places, thousands of kilometres away. The wind is responsible for lifting […]
Say that you have Sentinel-2 data and want to derive land cover classes from that data. You adopt a common pixel-based classification approach, say, Random Forest. You design a suitable classification scheme and give the training samples to the algorithm. The classification result is straightforward: all the classes are identified […]