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Relevant bibliographies by topics / Forest mapping Remote sensing Data processing

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Journal articles

Academic literature on the topic 'Forest mapping Remote sensing Data processing'

Author: Grafiati

Published: 11 December 2022

Last updated: 25 January 2023

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Journal articles on the topic "Forest mapping Remote sensing Data processing"

1

Artemeva, Olga, Aleksandr Bakulev, Natalya Pozdnyakova, and Sergey Tyurin. "Dynamic mapping of disturbed lands using remote sensing data." InterCarto. InterGIS 28, no. 2 (2022): 785–99. http://dx.doi.org/10.35595/2414-9179-2022-2-28-785-799.

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Due to the increase in the areas of disturbed lands, the relevance of developing methods and methods for obtaining and analyzing spatial data in order to make decisions on rational nature management is increasing every year. Monitoring of natural and anthropogenic systems is largely related to the collection, analysis and visualization of dynamic processes, so the technologies for compiling of dynamic maps are at the peak of relevance. A number of factors necessitate the using of dynamic geoimages. Firstly, these images are an inseparable combination of spatial-temporal links on the certain ar

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2

Parente, Leandro, Evandro Taquary, Ana Silva, Carlos Souza, and Laerte Ferreira. "Next Generation Mapping: Combining Deep Learning, Cloud Computing, and Big Remote Sensing Data." Remote Sensing 11, no. 23 (2019): 2881. http://dx.doi.org/10.3390/rs11232881.

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The rapid growth of satellites orbiting the planet is generating massive amounts of data for Earth science applications. Concurrently, state-of-the-art deep-learning-based algorithms and cloud computing infrastructure have become available with a great potential to revolutionize the image processing of satellite remote sensing. Within this context, this study evaluated, based on thousands of PlanetScope images obtained over a 12-month period, the performance of three machine learning approaches (random forest, long short-term memory-LSTM, and U-Net). We applied these approaches to mapped pastu

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Pasaribu, Roberto Patar, Aris Kabul Pranoto, Roni Sewiko, and Elfa Afwafiah. "MAPPING THE DISTRIBUTION OF MANGROVE BY REMOTE SENSING IN THE COASTAL OF KARAWANG REGENCY." Asian Journal of Aquatic Sciences 5, no. 2 (2022): 160–68. http://dx.doi.org/10.31258/ajoas.5.2.160-168.

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Mangroves are forest vegetation that grows between tidal lines so that mangrove forests are also called tidal forests. Mangrove ecosystems have high biodiversity. The mangrove ecosystem has a physical function to protect the coast from abrasion and erosion, this ecosystem also has ecological and economic value. The purpose of this study was to determine the condition and extent of mangrove distribution on the coast of Karawang Regency. The research was carried out on the coast of Karawang Regency from March to June 2021. The data used is primary data by directly observing the research location

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Wulder, Mike. "Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters." Progress in Physical Geography: Earth and Environment 22, no. 4 (1998): 449–76. http://dx.doi.org/10.1177/030913339802200402.

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Forests are the most widely distributed ecosystem on the earth, affecting the lives of most humans daily, either as an economic good or an environmental regulator. As forests are a complex and widely distributed ecosystem, remote sensing provides a valuable means of monitoring them. Remote-sensing instruments allow for the collection of digital data through a range of scales in a synoptic and timely manner. Accordingly, a variety of image-processing techniques have been developed for the estimation of forest inventory and biophysical parameters from remotely sensed images. The use of remotely

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Sanesi, Giovanni, Vincenzo Giannico, Mario Elia, and Raffaele Lafortezza. "Remote Sensing of Urban Forests." Remote Sensing 11, no. 20 (2019): 2383. http://dx.doi.org/10.3390/rs11202383.

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Urban forests and green infrastructures at large are of critical importance for contemporary cities as they provide a wide range of ecosystem services (ESS) that enhance the quality of life of urban dwellers. Remote sensing technologies have greatly contributed to assessing and mapping the spatial distribution of ESS in urban areas, although more research is needed given the availability of new sensors from multiple satellites and platforms and the particular characteristics of urban environments (e.g., high heterogeneity). This Special Issue hosts papers focusing on the temporal and spatial d

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6

Shihab, Tay H., Amjed N. Al-Hameedawi, and Ammar M. Hamza. "Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping." Engineering and Technology Journal 38, no. 4A (2020): 510–14. http://dx.doi.org/10.30684/etj.v38i4a.399.

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In this paper to make use of complementary potential in the mapping of LULC spatial data is acquired from LandSat 8 OLI sensor images are taken in 2019. They have been rectified, enhanced and then classified according to Random forest (RF) and artificial neural network (ANN) methods. Optical remote sensing images have been used to get information on the status of LULC classification, and extraction details. The classification of both satellite image types is used to extract features and to analyse LULC of the study area. The results of the classification showed that the artificial neural netwo

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7

Rokhmatuloh, Ardiansyah, Satria Indratmoko, Indra Riyanto, Lestari Margatama, and Rahmat Arief. "Burnt-Area Quick Mapping Method with Synthetic Aperture Radar Data." Applied Sciences 12, no. 23 (2022): 11922. http://dx.doi.org/10.3390/app122311922.

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Forest and field fires have become a frequent phenomenon in recent years caused by human activities in Indonesia, affecting all forms of forest and field cover. Forest fire-degraded land is more prone to burn again, due to the nature of peatland in Kalimantan. Rapid mapping technology for burnt areas affected by forest fires is needed to obtain this information. The use of remote sensing technology, in the form of synthetic aperture radar (SAR) images, combined with cloud computing processing speeds up data processing and is not affected by the existing cloud cover. The Quick-Mapping employed

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8

Kustiyo, K., O. Roswintiarti, A. Tjahjaningsih, R. Dewanti, S. Furby, and J. Wallace. "Annual Forest Monitoring as part of Indonesia's National Carbon Accounting System." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 441–48. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-441-2015.

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Land use and forest change, in particular deforestation, have contributed the largest proportion of Indonesia’s estimated greenhouse gas emissions. Indonesia’s remaining forests store globally significant carbon stocks, as well as biodiversity values. In 2010, the Government of Indonesia entered into a REDD+ partnership. A spatially detailed monitoring and reporting system for forest change which is national and operating in Indonesia is required for participation in such programs, as well as for national policy reasons including Monitoring, Reporting, and Verification (MRV), carbon accounting

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9

Amani, M., A. Ghorbanian, S. Mahdavi, and A. Mohammadzadeh. "IRANIAN LAND COVER MAPPING USING LANDSAT-8 IMAGERY AND RANDOM FOREST ALGORITHM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 77–81. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-77-2019.

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Abstract. Land cover classification is important for various environmental assessments. The opportunity of imaging the Earth’s surface makes remote sensing techniques efficient approaches for land cover classification. The only country-wide land cover map of Iran was produced by the Iranian Space Agency (ISA) using low spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and a basic classification method. Thus, it is necessary to produce a more accurate map using advanced remote sensing and machine learning techniques. In this study, multi-temporal Landsat-8 data (1

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10

Tarasov, Andrey V. "TRADITIONAL AND MODERN METHODS OF SATELLITE IMAGES PROCESSING FOR OPERATIONAL MAPPING OF FOREST COVER DISTUBANCES." Vestnik SSUGT (Siberian State University of Geosystems and Technologies) 25, no. 3 (2020): 201–13. http://dx.doi.org/10.33764/2411-1759-2020-25-3-201-213.

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Real-time mapping of forest disturbances is important for forest management. Detection of forest stands damaged by natural or human-induced factors allows making immediate necessary management decisions. To implement such a management strategy, it is necessary to use the methods of operational mapping. With the advent of the Earth remote sensing data (RSD), which have high spatial and temporal resolution (Planet Scope and Sentinel-2), it becomes possible to implement modern operational mapping methods for forest management operations (particularly, forest disturbance detection). Since the moni

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