CHINA FOREST COVER EXTRACTION BASED ON GOOGLE EARTH ENGINE

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

VHR Semantic Labeling by Random Forest Classification and Fusion of Spectral and Spatial Features on Google Earth Engine

Semantic labeling is an active field in remote sensing applications. Although handling high detailed objects in Very High Resolution (VHR) optical image and VHR Digital Surface Model (DSM) is a challenging task, it can improve the accuracy of semantic labeling methods. In this paper, a semantic labeling method is proposed by fusion of optical and normalized DSM data. Spectral and spatial featur...

متن کامل

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the...

متن کامل

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

Google Earth (GE) releases free images in high spatial resolution that may provide some potential for regional land use/cover mapping, especially for those regions with high heterogeneous landscapes. In order to test such practicability, the GE imagery was selected for a case study in Wuhan City to perform an object-based land use/cover classification. The classification accuracy was assessed b...

متن کامل

Investigation of land use changes in Gorganrood catchment using Google Earth Engine platform

The purpose of this study is to investigate landuse changes in Gorganrood basin in 2001, 2010 and 2019. Using Landsat and Product-Modes satellite images, used maps were prepared using the classification method of random forest algorithm in Google Earth Engine. Satellite imagery was classified into eight classes including forest, cropland, shrubland, grassland, wetland, urban, barren, and water....

متن کامل

Investigating and Assessing Soil's Texture and Density in Different Land Uses Via Google Earth Engine System

Introduction: Awareness of soil quality in agricultural lands and natural resources is essential to achieve maximum production and environmental sustainability. Although soil quality is not directly assessed, soil quality indicators are widely used today, including the physical indicators which are of great importance in measuring the soil quality, as they directly influence the plant growth an...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

سال: 2020

ISSN: 2194-9034

DOI: 10.5194/isprs-archives-xlii-3-w10-855-2020