Results 21 to 30 of about 2,899 (211)

Landsat-MODIS image fusion and object-based image analysis for observing flood inundation in a heterogeneous vegetated scene

GIScience & Remote Sensing, 2019
Typhoon flooding normally occurs suddenly with short duration, and the thick cloud cover limits the ability of one single satellite to timely capture the inundation extent.
Phuong D. Dao, Ngoc Thi Mong, Hai-Po Chan   +2 more
doaj   +1 more source

Comparing fully convolutional networks, random forest, support vector machine, and patch-based deep convolutional neural networks for object-based wetland mapping using images from small unmanned aircraft system

GIScience & Remote Sensing, 2018
Deep learning networks have shown great success in several computer vision applications, but its implementation in natural land cover mapping in the context of object-based image analysis (OBIA) is rarely explored area especially in terms of the impact ...
Tao Liu, Amr Abd-Elrahman, Jon Morton, Victor L. Wilhelm   +3 more
doaj   +1 more source

Evaluation of Above-Ground Carbon Sequestration of Forest in Mahasarakham University Using Remote Sensing Data [PDF]

Warasan Witthayasat Lae Theknoloyi Mahawitthayalai Mahasarakham, 2020
At present, the increase of greenhouse gas has led to anincrease in global temperature. This problem can be solved by extending green areas to reduce the amount of gas.
Jaturong Som-ard
doaj  

A comparison of unsupervised segmentation parameter optimization approaches using moderate- and high-resolution imagery

GIScience & Remote Sensing, 2017
Unsupervised segmentation optimization methods have been proposed to aid in selecting an “optimal” set of scale parameters quickly and objectively for object-based image analysis.
Heather Grybas, Lindsay Melendy, Russell G. Congalton   +2 more
doaj   +1 more source

New Tools for the Classification and Filtering of Historical Maps

ISPRS International Journal of Geo-Information, 2019
Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi-
Stefano Gobbi, Marco Ciolli, Nicola La Porta, Duccio Rocchini, Clara Tattoni, Paolo Zatelli   +5 more
doaj   +1 more source

Toward the automatic detection of effective gerbil holes in desert grasslands through unmanned aerial vehicle imagery

Geocarto International, 2023
Rapidly determining the density of effective gerbil holes is ecologically important but technically challenging. However, unmanned aerial vehicles (UAVs) offer new methods to identify effective gerbil holes and understand the spatial relationships ...
Guimei Qi, Zhihong Yu, Zhenjie Hou, Ying Guo, Billiger Huth   +4 more
doaj   +1 more source

Multi-Regional landslide detection using combined unsupervised and supervised machine learning

Geomatics, Natural Hazards & Risk, 2021
Landslide detection is concerned with delineating the extent of landslides. Most of existing works on landslide detection have limited geographical extents. Therefore, the models developed out of these studies might perform poorly when applied to regions
Faraz S. Tehrani, Giorgio Santinelli, Meylin Herrera Herrera   +2 more
doaj   +1 more source

Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study

GIScience & Remote Sensing, 2023
Invasive alien plant species (IAPS) have negative impacts on ecosystems, including the loss of biodiversity and the alteration of ecosystem functions. The strategy for mitigating these impacts requires knowledge of these species’ spatial distribution and
Fiston Nininahazwe, Jérôme Théau, Genest Marc Antoine, Mathieu Varin   +3 more
doaj   +1 more source

Self-Adaptive-Filling Deep Convolutional Neural Network Classification Method for Mountain Vegetation Type Based on High Spatial Resolution Aerial Images

Remote Sensing, 2023
The composition and structure of mountain vegetation are complex and changeable, and thus urgently require the integration of Object-Based Image Analysis (OBIA) and Deep Convolutional Neural Networks (DCNNs). However, while integration technology studies
Shiou Li, Xianyun Fei, Peilong Chen, Zhen Wang, Yajun Gao, Kai Cheng, Huilong Wang, Yuanzhi Zhang   +7 more
doaj   +1 more source

Efficient paddy field mapping using Landsat-8 imagery and object-based image analysis based on advanced fractel net evolution approach

GIScience & Remote Sensing, 2017
This paper proposes an efficient paddy field mapping method using object-based image analysis and a bitemporal data set acquired by Landsat-8 Operational Land Imager.
Tengfei Su
doaj   +1 more source