Worldview-2 and Landsat 8 Satellite Data for Seaweed Mapping along Karachi Coast

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Muhammad Danish Siddiqui ◽  
Arjumand Z Zaidi
Keyword(s):  
Satellite Data ◽  
Spatial Scales ◽  
Economic Value ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Geographical Information ◽  
Landsat 8 ◽  
Coverage Area ◽  
Breeding Sites ◽  
Marine Plant

<span>Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of <span>this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite <span>data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastal<br /><span>waters of Karachi. The continuous monitoring and mapping of this precious marine plant and their <span>breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote <span>Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient <span>solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both <span>temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image <span>enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of <span>seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation <span>wasachieved with WV-2 data that shows 15.5Ha (0.155 Km<span>2<span>)of seaweed cover along Karachi coast that is <span>more representative of the field observed data. A much larger area wasestimated with Landsat 8 image <span>(71.28Ha or 0.7128 Km<span>2<span>) that was mainly due to the mixing of seaweed pixels with water pixels. The <span>WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat<br /><span>8 in mapping seaweed patches</span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span>

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.  

Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices

2021 ◽  
Vol 25 (9) ◽  
pp. 30-37
Author(s):  
N.N. Sliusar ◽  
A.P. Belousova ◽  
G.M. Batrakova ◽  
R.D. Garifzyanov ◽  
M. Huber-Humer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Google Earth ◽  
The State ◽  
Landsat 8 ◽  
The Earth

The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.

scholarly journals Soil Moisture Retrieval from the Chinese GF-3 Satellite and Optical Data over Agricultural Fields

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2675 ◽  
Author(s):  
Linlin Zhang ◽  
Qingyan Meng ◽  
Shun Yao ◽  
Qiao Wang ◽  
Jiangyuan Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Satellite Data ◽  
Cloud Model ◽  
Vegetation Indices ◽  
Bare Soil ◽  
Optical Data ◽  
Retrieval Algorithm ◽  
Landsat 8 ◽  
Backscattering Coefficient ◽  
Vegetation Water

Timely and accurate soil moisture information is of great importance in agricultural monitoring. The Gaofen-3 (GF-3) satellite, the first C-band multi-polarization synthetic-aperture radar (SAR) satellite in China, provides valuable data sources for soil moisture monitoring. In this study, a soil moisture retrieval algorithm was developed for the GF-3 satellite based on a backscattering coefficient simulation database. We adopted eight optical vegetation indices to determine the relationships between these indices and vegetation water content (VWC) by combining Landsat-8 data and field measurements. A backscattering coefficient database was built using an advanced integral equation model (AIEM). The effects of vegetation on backscattering coefficients were corrected using the water cloud model (WCM) to obtain the bare soil backscattering coefficient ( σ s o i l ° ). Then, soil moisture retrievals were obtained at HH, VV and HH+VV combination respectively by minimizing the observed bare soil backscattering coefficient ( σ s o i l ° ) and the AIEM-simulated backscattering coefficient ( σ soil-simu ° ). Finally, the proposed algorithm was validated in agriculture region of wheat and corn in China using ground soil moisture measurements. The results showed that the normalized difference infrared index (NDII) had the best fit with measured VWC values (R = 0.885) among the eight vegetation water indices; thus, it was adopted to correct the effects of vegetation. The proposed algorithm using GF-3 satellite data performed well in soil moisture retrieval, and the scheme combining HH and VV polarization exhibited the highest accuracy, with a root mean square error (RMSE) of 0.044 m3m−3, followed by HH polarization (RMSE = 0.049 m3m−3) and VV polarization (RMSE = 0.053 m3m−3). Therefore, the proposed algorithm has good potential to operationally estimate soil moisture from the new GF-3 satellite data.

scholarly journals Determining the Vegetation Indices (NDVI) from Landsat 8 Satellite Data.

2016 ◽  
Vol 4 (8) ◽  
pp. 1459-1463 ◽  
Author(s):  
MushtaqAhmad Ganie ◽  
◽  
Dr.Asima Nusrath ◽  
Keyword(s):  
Satellite Data ◽  
Vegetation Indices ◽  
Landsat 8

scholarly journals Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

2020 ◽  
Vol 12 (4) ◽  
pp. 660 ◽  
Author(s):  
Jonathan Peereman ◽  
James Aaron Hogan ◽  
Teng-Chiu Lin
Keyword(s):  
Forest Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landscape Heterogeneity ◽  
Spatial Scales ◽  
Vegetation Indices ◽  
Permanent Plots ◽  
Forest Plot ◽  
Landsat 8 ◽  
Four Square

Permanent forest dynamics plots have provided valuable insights into many aspects of forest ecology. The evaluation of their representativeness within the landscape is necessary to understanding the limitations of findings from permanent plots at larger spatial scales. Studies on the representativeness of forest plots with respect to landscape heterogeneity and disturbance effect have already been carried out, but knowledge of how multiple disturbances affect plot representativeness is lacking—particularly in sites where several disturbances can occur between forest plot censuses. This study explores the effects of five typhoon disturbances on the Fushan Forest Dynamics Plot (FFDP) and its surrounding landscape, the Fushan Experimental Forest (FEF), in Taiwan where typhoons occur annually. The representativeness of the FFDP for the FEF was studied using four topographical variables derived from a digital elevation model and two vegetation indices (VIs), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII), calculated from Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data. Representativeness of four alternative plot designs were tested by dividing the FFDP into subplots over wider elevational ranges. Results showed that the FFDP neither represents landscape elevational range (<10%) nor vegetation cover (<7% of the interquartile range, IQR). Although disturbance effects (i.e., ΔVIs) were also different between the FFDP and the FEF, comparisons showed no under- or over-exposure to typhoon damage frequency or intensity within the FFDP. In addition, the ΔVIs were of the same magnitudes in the plots and the reserve, and the plot covered 30% to 75.9% of IQRs of the reserve ΔVIs. Unexpectedly, the alternative plot designs did not lead to increased representation of damage for 3 out of the 4 tested typhoons and they did not suggest higher representativeness of rectangular vs. square plots. Based on the comparison of mean Euclidian distances, two rectangular plots had smaller distances than four square or four rectangular plots of the same area. Therefore, this study suggests that the current FFDP provides a better representation of its landscape disturbances than alternatives, which contained wider topographical variation and would be more difficult to conduct ground surveys. However, upscaling needs to be done with caution as, in the case of the FEF, plot representativeness varied among typhoons.

scholarly journals Pemanfaatan Citra Satelit Penginderaan Jauh dan Sistem Informasi Geografi Untuk Analisis Nilai Ekonomi Ekosistem Pesisir. Studi kasus: Desa Teluk Limau, Kecamatan Jebus, Kabupaten Bangka Barat, Provinsi Bangka Belitung

2020 ◽  
Vol 5 (1) ◽  
pp. 33
Author(s):  
Bayu Prayudha ◽  
Muhammad Hafizt ◽  
Indra Bayu Vimono
Keyword(s):  
Remote Sensing ◽  
Spatial Information ◽  
Economic Value ◽  
Coastal Region ◽  
Coastal Ecosystems ◽  
Coastal Ecosystem ◽  
Geographical Information ◽  
Landsat 8 ◽  
Value Analysis ◽  
Spatial Parameters

<p class="Papertext"><strong>The Application of Remote Sensing and Geographical Information System (GIS) for Economic Value Analysis of Coastal Ecosystem</strong><strong>. Case Study: Teluk Limau Vilage, Jebus District, West Bangka Regency, Bangka Belitung Province</strong>. Coral reefs, seagrass, and mangroves are important ecosystems as the source of nutrients and as the habitat provider for marine biotas. Sustainability of those ecosystems is important for Indonesians while many of them lived in the coastal region. However, information on those ecosystems is still lacked, because most of the area is difficult to reach. Remote sensing would provide a possibility to address the problem. Remote sensing can present a spatial description of a certain area, so it gives a better understanding for the policy maker to manage their area. One of the utilization of this information is to calculate the economic value of coastal ecosystems. The valuation would involve spatial parameters of both the extent of habitat and the length of ecosystem-protected coastline as a multiplier factor. Those parameters can be obtained quickly, easily and accurately using remote sensing. The purpose of this research is to apply remote sensing data for the economic valuation of coastal ecosystems. The method used was the combination of image processing of LANDSAT-8 satellite data and GIS to calculate spatial parameters of habitat, and surrogate market prices approach to assess the economic value of the ecosystems. The research was conducted in Teluk Limau Village, Jebus District, West Bangka Regency, Babel Province. This research has mapped four habitat classes of the coastal ecosystem including coral, macroalgae bed, bare substrate, and mangrove. Based on the spatial information of the map, the economic value of coral reef and mangrove was 141.4 billion rupiahs and 31.1 billion rupiahs respectively.</p>

scholarly journals Assessing Riparian Areas of Greece—An Overview

2020 ◽  
Vol 13 (1) ◽  
pp. 309
Author(s):  
George N. Zaimes ◽  
Valasia Iakovoglou
Keyword(s):  
Sustainable Management ◽  
Stream Flow ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Assessment Tools ◽  
Land Uses ◽  
Riparian Areas ◽  
Spatial And Temporal Scales ◽  
Management Plans ◽  
Of Greece

Riparian areas, especially in the Mediterranean, offer many ecosystem services for the welfare of society benefits from their sustainable management. This study presents different tools used to assess riparian areas of Greece and their results. Riparian areas with different land-uses/vegetation covers along streams or torrents were assessed. The assessment tools were visual protocols, bioindicators, geographic information systems (GIS), vegetation indices, and a model. These tools differ in scale, accuracy, and difficulty of implementation. The riparian areas had Low and Moderate quality in Greece because of agricultural activities and hydrologic alterations. Vegetation appeared more important for the integrity of riparian areas than stream flow (perennial or intermittent). In addition, territorial variables (distance from dam and sea) were more influential compared to climatic variables. Visual protocols and GIS were effective for preliminary assessments. GIS can be applied at a greater scale but was less accurate than the protocols. Bioindicators can provide more cost-effective monitoring than physicochemical water variables. Finally, vegetation indices and models can be used for larger spatial and temporal scales, but require specialized personnel. Overall, riparian areas of Greece seem to be degraded, and monitoring would contribute to the development of a database on riparian areas that should form the basis for sustainable management plans in Greece.

scholarly journals Fengyun Meteorological Satellite Products for Earth System Science Applications

2021 ◽  
Author(s):  
Di Xian ◽  
Peng Zhang ◽  
Ling Gao ◽  
Ruijing Sun ◽  
Haizhen Zhang ◽  
...  
Keyword(s):  
Data Sharing ◽  
Satellite Data ◽  
Prediction Models ◽  
Weather Forecasting ◽  
Numerical Models ◽  
Weather Prediction ◽  
Vegetation Indices ◽  
Open Data ◽  
Earth System ◽  
Inversion Algorithm

AbstractFollowing the progress of satellite data assimilation in the 1990s, the combination of meteorological satellites and numerical models has changed the way scientists understand the earth. With the evolution of numerical weather prediction models and earth system models, meteorological satellites will play a more important role in earth sciences in the future. As part of the space-based infrastructure, the Fengyun (FY) meteorological satellites have contributed to earth science sustainability studies through an open data policy and stable data quality since the first launch of the FY-1A satellite in 1988. The capability of earth system monitoring was greatly enhanced after the second-generation polar orbiting FY-3 satellites and geostationary orbiting FY-4 satellites were developed. Meanwhile, the quality of the products generated from the FY-3 and FY-4 satellites is comparable to the well-known MODIS products. FY satellite data has been utilized broadly in weather forecasting, climate and climate change investigations, environmental disaster monitoring, etc. This article reviews the instruments mounted on the FY satellites. Sensor-dependent level 1 products (radiance data) and inversion algorithm-dependent level 2 products (geophysical parameters) are introduced. As an example, some typical geophysical parameters, such as wildfires, lightning, vegetation indices, aerosol products, soil moisture, and precipitation estimation have been demonstrated and validated by in-situ observations and other well-known satellite products. To help users access the FY products, a set of data sharing systems has been developed and operated. The newly developed data sharing system based on cloud technology has been illustrated to improve the efficiency of data delivery.

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