FOREST COVER CLASSIFICATION USING GEOSPATIAL MULTIMODAL DATA

نویسندگان
چکیده

برای دانلود رایگان 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

Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data

Environmental limiting factors (ELFs) are the thresholds that determine the maximum or minimum biological response for a given suite of environmental conditions. We asked the following questions: 1) Can we detect ELFs on percent tree cover across the eastern slopes of the Lake Tahoe Basin, NV? 2) How are the ELFs distributed spatially? 3) To what extent are unmeasured environmental factors limi...

متن کامل

Urban Land Cover Classification Using Hyperspectral Data

Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...

متن کامل

forest stand age classification using landsat etm+ data

classifying age classes in a large area using remotely sensed data has considerable significance for forest sustainable management. in this research, landsat etm+ data from loveh forest, dating july 2002, were analyzed to investigate the potential of this sensor for age class mapping. we applied a systematic cluster sampling method to collect field data. we used 99 plots so that contained 32 pl...

متن کامل

Forest Stand Types Classification Using Tree-Based Algorithms and SPOT-HRG Data

Forest types mapping, is one of the most necessary elements in the forest management and silviculture treatments. Traditional methods such as field surveys are almost time-consuming and cost-intensive. Improvements in remote sensing data sources and classification –estimation methods are preparing new opportunities for obtaining more accurate forest biophysical attributes maps. This research co...

متن کامل

Random Forest Algorithm for Land Cover Classification

Since the launch of the first land observation satellite Landsat-1 in 1972, many machine learning algorithms have been used to classify pixels in Thematic Mapper (TM) imagery. Classification methods range from parametric supervised classification algorithms such as maximum likelihood, unsupervised algorithms such as ISODAT and k-means clustering to machine learning algorithms such as artificial...

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: 2018

ISSN: 2194-9034

DOI: 10.5194/isprs-archives-xlii-2-1091-2018