scholarly journals Identifying mangrove forests using radar remote sensing data

2016 ◽  
Vol 19 (2) ◽  
pp. 113-121
Author(s):  
Phung Phi Hoang ◽  
Nguyen Dao Lam ◽  
Viet Bach Pham
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Mangrove Forests ◽  
Dual Polarization ◽  
Alos Palsar ◽  
Radar Remote Sensing ◽  
Envisat Asar ◽  
Cover Density ◽  
Level Identification

Mangrove is one of the ecologically significant ecosystems in coastal areas, both on environment and biological resources. Radar remote sensing demonstrates a high potential in detecting, identifying, mapping and monitoring mangrove forests. Advantages of radar remote sensing are that almost unaffected by the weather phenomena in the atmosphere, e.g. clouds so that it can acquire images at day and night times. This study considers possibilities of ALOS PALSAR (L-band) and ENVISAT ASAR APP (C-band) for identifying mangrove forests. Results show that using single-date data of ENVISAT ASAR APP including dual polarization HH&HV are difficult to classify mangrove objects; whilst single-date data of ALOS PALSAR with dual polarization HH&HV have a better classification for tree density but at species level identification (e.g. Avicenna or Rhizophora) is more difficult. Results classified according to forest cover density data with overall accuracy of 81.91.

Small-scale vegetation mapping of large territories: perspectives of using modern remote sensing and GIS technologies, the Indian experiences

1996 ◽  
pp. 51-54 ◽  
Author(s):  
N. V. M. Unni
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Forest Cover ◽  
Human Life ◽  
Remote Sensing Data ◽  
Modern World ◽  
Small Scale ◽  
Vegetation Map ◽  
Gis Technologies ◽  
Forest Cover Mapping

The recognition of versatile importance of vegetation for the human life resulted in the emergence of vegetation science and many its applications in the modern world. Hence a vegetation map should be versatile enough to provide the basis for these applications. Thus, a vegetation map should contain not only information on vegetation types and their derivatives but also the geospheric and climatic background. While the geospheric information could be obtained, mapped and generalized directly using satellite remote sensing, a computerized Geographic Information System can integrate it with meaningful vegetation information classes for large areas. Such aft approach was developed with respect to mapping forest vegetation in India at. 1 : 100 000 (1983) and is in progress now (forest cover mapping at 1 : 250 000). Several review works reporting the experimental and operational use of satellite remote sensing data in India were published in the last years (Unni, 1991, 1992, 1994).

scholarly journals Capacity Development for Use of Remote Sensing for REDD+ MRV Using Online and Offline Activities: Impacts and Lessons Learned

2021 ◽  
Vol 13 (11) ◽  
pp. 2172
Author(s):  
Sarah Carter ◽  
Martin Herold ◽  
Inge Jonckheere ◽  
Andres Espejo ◽  
Carly Green ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Hybrid Approach ◽  
Remote Sensing Data ◽  
Lessons Learned ◽  
Multiple Partners ◽  
Large Audience ◽  
Forest Cover Changes ◽  
The Impact ◽  
And Training

Four workshops and a webinar series were organized, with the aim of building capacity in countries to use Earth Observation Remote Sensing data to monitor forest cover changes and measure emissions reductions for REDD+ results-based payments. Webinars and workshops covered a variety of relevant tools and methods. The initiative was collaboratively organised by a number of Global Forest Observations Initiative (GFOI) partner institutions with funding from the World Bank’s Forest Carbon Partnership Facility (FCPF). The collaborative approach with multiple partners proved to be efficient and was able to reach a large audience, particularly in the case of the webinars. However, the impact in terms of use of tools and training of others after the events was higher for the workshops. In addition, engagement with experts was higher from workshop participants. In terms of efficiency, webinars are significantly cheaper to organize. A hybrid approach might be considered for future initiatives; and, this study of the effectiveness of both in-person and online capacity building can guide the development of future initiatives, something that is particularly pertinent in a COVID-19 era.

Remote sensing and GIS forest landscape assessment for sustainable forest management

2021 ◽  
Vol 17 (1) ◽  
pp. 12-26
Author(s):  
A.F. Chukwuka ◽  
A. Alo ◽  
O.J. Aigbokhan
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Markov Chain Model ◽  
Remote Sensing Data ◽  
Chain Model ◽  
Spatial Metrics ◽  
Forest Reserve ◽  
Land Cover Types

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment. Keyword: Landscape, Spatial metrics, sustainable forest and Environment

scholarly journals Evaluating the environmental impact of payments for ecosystem services in Coatepec (Mexico) using remote sensing and on-site interviews

2011 ◽  
Vol 38 (4) ◽  
pp. 426-434 ◽  
Author(s):  
JASON SCULLION ◽  
CRAIG W. THOMAS ◽  
KRISTINA A. VOGT ◽  
OCTAVIO PÉREZ-MAQUEO ◽  
MILES G. LOGSDON
Keyword(s):  
Remote Sensing ◽  
Ecosystem Services ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Environmental Benefits ◽  
Payments For Ecosystem Services ◽  
Programme Implementation ◽  
Before And After ◽  
Monitoring And Enforcement ◽  
Landsat Satellite

SUMMARYOver the last decade, hundreds of payments for ecosystem services (PES) programmes have been initiated around the world, but evidence of their environmental benefits remains limited. In this study, two PES programmes operating in the municipality of Coatepec (Mexico) were evaluated to assess their effectiveness in protecting the region's endangered upland forests. Landsat satellite data were analysed to assess changes in forest cover before and after programme implementation using a difference-in-differences estimator. Additionally, surveys and interviews were conducted with local residents and a subset of PES programme participants to evaluate the programmes’ social and environmental impacts, particularly the effect of the programmes on landowner behaviour. The remote-sensing data show that deforestation was substantially lower on properties receiving PES payments compared to properties not enrolled in the programmes, but the programmes did not prevent the net loss of forests within Coatepec. Moreover, the on-site interviews suggest that the payments may have had little impact on deforestation rates, and that other factors contributed to the conservation of forests in PES properties. These findings suggest that risk-targeted payments, robust monitoring and enforcement programmes, and additional conservation initiatives should be included in all PES schemes to ensure environmental effectiveness.

scholarly journals Forest areas remote monitoring within the limits of transport objects impact

2021 ◽  
pp. 109-118
Author(s):  
Dmytro Liashenko ◽  
◽  
Dmytro Pavliuk ◽  
Vadym Belenok ◽  
Vitalii Babii ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Remote Monitoring ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Remote Sensing Data ◽  
Transport Infrastructure ◽  
Nature Management ◽  
Collecting Methods ◽  
Remote Sensing Methods

The article studies the issues of using remote sensing data for the tasks of ensuring sustainable nature management in the territories within the influence of transport infrastructure objects. Peculiarities of remote monitoring for tasks of transport networks design and in the process of their operation are determined. The paper analyzes the development of modern remote sensing methods (satellite imagery, the use of mobile sensors installed on cars or aircraft). A brief overview of spatial data collecting methods for the tasks of managing the development of territories within the influence of transport infrastructure (roads, railways, etc.) has made. The article considers the experience of using remote sensing technologies to monitor changes in the parameters of forest cover in the Transcarpathian region (Ukraine) in areas near to highways, by use Landsat imagery.

scholarly journals A study on deforestation in hilly areas of Haryana using Remote Sensing and GIS technique

2020 ◽  
pp. 69-77
Author(s):  
Anju Jangra ◽  
Anurag Airon ◽  
Ram Niwas
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Geographical Information ◽  
Special Focus ◽  
Landsat 8 ◽  
Deforestation Rate ◽  
Gis Technique ◽  
Prime Concern

Forest is an essential part or backbone of the earth ecological system. In a country like India, the people and the economy of nation is mainly relies on the diversity of natural resources. In today's world degradation of forest resources is a prime concern for many of the scientists and environmentalists because the canvas had been transformed from last few decades to cultivated and non-cultivated land. In India, Haryana state has lowest forest cover i.e. 3.59% followed by Punjab 3.65%. Over the several decades, the advancement of Remote Sensing and Geographical Information System (GIS) technique has emerged as an efficient tool to monitor and analyse deforestation rate in hilly areaor over a variety of location. Remote sensing based vegetation indices show better sensitivity than individual band reflectance and hence are more preferred for assessment and monitoring of tress. The aim of the present study was to analyse the deforestation in hilly areas in Haryana State (India) by remote sensing data with a special focus on Panchkula and Yamunanagar. The information was collected through the LANDSAT 8 satellite of NASA. The result revealed that the deforestation rate is high in Hilly areas of Haryana. The study shows that the forest cover in hilly areas of Haryana in 2013 was 50,879.07 hectares and in 2019 it was 44,445.51 hectares of land. Thereby decrease in forest cover of 6,433.56 hectares had been observed in the study period of 2013-2019 i.e. 6 years. Spatial variations in deforestation were also mapped in GIS for the hilly areas in Panchkula and Yamunanagar districts of Haryana.  

Application of optical and radar data for lineaments mapping in Kerdous inlier of the Anti Atlas belt, Morocco

2021 ◽  
Author(s):  
Amine Jellouli ◽  
Abderrazak El Harti ◽  
Zakaria Adiri ◽  
Mohcine Chakouri ◽  
Jaouad El Hachimi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Ore Deposits ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Alos Palsar ◽  
Geological Map ◽  
Color Composite ◽  
Manual Extraction

<p>Lineament mapping is an important step for lithological and hydrothermal alterations mapping. It is considered as an efficient research task which can be a part of structural investigation and mineral ore deposits identification. The availability of optical as well as radar remote sensing data, such as Landsat 8 OLI, Terra ASTER and ALOS PALSAR data, allows lineaments mapping at regional and national scale. The accuracy of the obtained results depends strongly on the spatial and spectral resolution of the data. The aim of this study was to compare Landsat 8 OLI, Terra ASTER, and radar ALOS PALSAR satellite data for automatic and manual lineaments extraction. The module Line of PCI Geomatica software was applied on PC1 OLI, PC3 ASTER and HH and HV polarization images to automatically extract geological lineaments. However, the manual extraction was achieved using the RGB color composite of the directional filtered images N - S (0°), NE - SW (45°) and E - W (90°) of the OLI panchromatic band 8. The obtained lineaments from automatic and manual extraction were compared against the faults and photo-geological lineaments digitized from the existing geological map of the study area. The extracted lineaments from PC1 OLI and ALOS PALSAR polarizations images showed the best correlation with faults and photo-geological lineaments. The results indicate that the lineaments extracted from HH and HV polarizations of ALOS PALSAR radar data used in this study, with 1499 and 1507 extracted lineaments, were more efficient for structural lineament mapping, as well as the PC1 OLI image with 1057 lineaments.</p><p><strong>Keywords</strong> Remote Sensing . OLI. ALOS PALSAR . ASTER . Kerdous Inlier . Anti Atlas</p>

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