The present study was carried out to produce and evaluate the land use/land cover maps by on screen visual interpretation. The studies of land cover of Allahabad city (study area) consist of 87517.47 ha out of which 5500.35 ha is build up land (Urban / Rural) Area. In this respect, ...
Deep learning-based segmentation of very high-resolution (VHR) satellite images is a significant task providing valuable information for various geospatial applications, specifically for land use/land cover (LULC) mapping. The segmentation task becomes more challenging with the increasing number and comple...
land use and land cover mapping; remote sensing; machine learning; deep learning; geospatial big data1. Introduction Accurate and timely land use and land cover (LULC) maps are important for a variety of applications such as urban and regional planning, disasters and hazards monitoring, natural ...
Land use/Land cover maps are a snapshot in time, but natural processes and human activity can rapidly change the landscape. Too often, map availability can lag several years behind data acquisition. However, with the unique deep learning approach used to create the Sentinel-2 10m Land Use/Lan...
The LULC Map on Demand provides users with a custom map of land use/land cover for a user-specified area of interest and time period (2018-2022). The map is derived from ESA Sentinel-2 imagery at 10m resolution. It is a composite of LULC predictions
This paper presents a dataset of yearly land use and land cover classification maps for Mato Grosso State, Brazil, from 2001 to 2017. Mato Grosso is one of the world’s fast moving agricultural frontiers. To ensure multi-year compatibility, the work uses
REDLANDS, Calif.—February 8, 2023—Land Use/Land Cover (LULC) maps are an increasingly important tool for decision-makers at local, regional, and national government levels around the world. These maps help inform policy and land management decisions around issues like sustainab...
For proper planning of urban infrastructures such as road networks, pipelines, and other linear engineering structures, it is necessary to construct precise land use and land cover maps. Multiple attempts to develop land use land cover classification techniques have been made using various methods rang...
These 30-meter resolution land cover maps show the global distribution of 10 major land cover classes: water bodies, wetlands, artificial surfaces, cultivated land, permanent snow and ice, forests, grasslands, shrubland, bare land, and tundra. ...
Regularly updated global land use land cover (LULC) datasets provide the basis for understanding the status, trends, and pressures of human activity on carbon cycles, biodiversity, and other natural and anthropogenic processes1,2,3. Annual maps of global LULC have been developed by many groups. ...