Study on remote sensing classification of land-use based on FNEA & D-S

2011 ◽  
Author(s):  
Haiqing He ◽  
Shengxiang Huang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Classification

Based on IDRISI Remote Sensing Images Land-Use Types of Supervised Classification Techniques

2013 ◽  
Vol 415 ◽  
pp. 305-308
Author(s):  
Kun Zhang ◽  
Hai Feng Wang ◽  
Zhuang Li
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Classification Techniques ◽  
Analysis And Evaluation ◽  
Remote Sensing Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Image Classification ◽  
Land Use Types ◽  
Area Distribution

With remote sensing technology and computer technology, remote sensing classification technology has been rapid progress. In the traditional classification of remote sensing technology, based on the combination of today's technology in the field of remote sensing image classification, some new developments and applications for land cover classification techniques to make more comprehensive elaboration. Using the minimum distance classifier extracts of the study area land use types. Ultimately extracted land use study area distribution image and make its analysis and evaluation.

Water Accounting Plus (WA+) through Remote Sensing in the Yarmouk Tributary Basin

2021 ◽  
Author(s):  
Chadi Abdallah ◽  
Gina Tarhini ◽  
Mariam Daher ◽  
Hussein Khatib ◽  
Mark Zeitoun
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Management Strategies ◽  
Initial Distribution ◽  
Yarmouk River ◽  
The Status ◽  
Irrigated Crops ◽  
Water Accounting ◽  
Derived Data

<p>Coping with the issue of water scarcity and growing competition for water among different sectors requires effective water management strategies and decision processes. ‘Getting it right’ becomes doubly important when dealing with intenational transboundary rivers. The Yarmouk tributary to the Jordan River is one highly exploited in the Middle East, and is enveloped by ambiguous treaties and decades of violent and non-violent conflict. Seeking to chart a more sustainable and equitable future, this work performs a 'water accounting plus' methodology employing readily available remotely sensed satellite-based data coupled with available measurements.  A variety of methods described herein were used to detect irrigated crops and produce maps showing the distribution throughout the basin. The framework also focuses on the classification of land use categories and the processes by which water is depleted over all land use classes that contributes to separate the beneficial from non-beneficial usage of water. The analysis was started prior to the 2011 start of the Syrian war in order to study the initial distribution of land use classes as well as the water depletion processes before any change in the basin. It shows that more than half of the exploitable water is not consumed within the basin and depleted outside. In contrast, most of the water consumed within the basin is wasted and depleted in a non-beneficial way. Roughly 35% of the cultivated area shown to be irrigated through withdrawals which exceed the capacity of the source. This result reflects the high abstraction rates from groundwater via a large number of unlicensed wells mostly located at the Syrian side. This study also detect a deficiency in the water balance of the Yarmouk River. The findings are relevant to sustainable management not only for water-dependent sectors but also for geopolitical stability among the riparian countries. In this way, open- access remote sensing derived data can provide useful information about the status of water resources especially when ground measurements are poor or absent.</p><p> </p><p>Keywords: Yarmouk, Water Accounting Plus, IWM, Irrigated crops, WAPOR.</p>

Remote Sensing Classification of Marsh Wetland with Different Resolution Images

2016 ◽  
Vol 7 (2) ◽  
pp. 107-114 ◽  
Author(s):  
Li Na ◽  
Xie Gaodi ◽  
Zhou Demin ◽  
Zhang Changshun ◽  
Jiao Cuicui
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Classification ◽  
Marsh Wetland

Classification of land use areas using remote sensing data with machine learning

2020 ◽  
Author(s):  
Mustapha Skittou ◽  
Ouadia Madhoum ◽  
Abdelouahab Khannouss ◽  
Mohamed Merrouchi ◽  
Taoufiq Gadi
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Sensing Data

Abstracting of suspected illegal land use in urban areas using case-based classification of remote sensing images

2008 ◽  
Author(s):  
Fulong Chen ◽  
Chao Wang ◽  
Chengyun Yang ◽  
Hong Zhang ◽  
Fan Wu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Areas ◽  
Remote Sensing Images ◽  
Case Based
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