Spotting Green Tides over Brittany from Space: Three Decades of Monitoring with Landsat Imagery

Green tides of macroalgae have been negatively affecting the coasts of Brittany, France, for at least five decades, caused by excessive nitrogen inputs from the farming sector. Regular areal estimates of green tide surfaces are publicly available but only from 2002 onwards. Using free and openly accessible Landsat satellite imagery archives over 35 years (1984–2019), this study explores the potential of remote sensing for detection and long-term monitoring of green macroalgae blooms. By using a Google Earth Engine (GEE) script, we were able to detect and quantify green tide surfaces using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) at four highly affected beaches in Northern Brittany. Mean green tide coverage was derived and analyzed from 1984 to 2019, at both monthly and annual scales. Our results show important interannual and seasonal fluctuations in estimated macroalgae cover. In terms of trends over time, green tide events did not show a decrease in extent at three out of four studied sites. The observed decrease in nitrogen concentrations for the rivers draining the study sites has not resulted in a reduction of green tide extents.

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INVESTIGATION OF THE CHANGES OF LAKE SURFACE TEMPERATURES AND AREAS: CASE STUDY OF BURDUR AND EGIRDIR LAKES, TURKEY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b3-2021-299-2021 ◽

2021 ◽

Vol XLIII-B3-2021 ◽

pp. 299-304

Author(s):

N. Aslan ◽

D. Koc-San

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Aquatic Systems ◽

Lake Area ◽

Lake Surface ◽

Water Index ◽

Time Period ◽

Eğirdir Lake ◽

Egirdir Lake ◽

Landsat Satellite

Abstract. The world's average surface temperature has been increasing in recent decades. This situation is expected to affect aquatic systems and lakes are one of the most important aquatic systems. The main aims of this study are to examine Lake Surface Water Temperature (LSWT) and area changes of Burdur and Egirdir lakes located in the West Mediterranean Region (TR61) of Turkey for the years 1998, 2008 and 2018 using Landsat satellite images. For this purpose, initially, Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) images were generated and the lake shorelines were extracted by thresholding these images. Then, the LSWT values were obtained by using Landsat thermal images. Finally, the area and LSWT changes of Burdur and Egirdir lakes between the years 1998-2008-2018 and the relationships of these parameters with each other were analysed. The obtained results showed that the lake boundaries could be semi-automatically extracted with overall accuracy values higher than 95%. In 20-year time period it was also observed that the Burdur Lake area decreased significantly, while the Egirdir Lake area decreased slightly. When the LSWT values were analysed, it can be stated that the LSWT values increased in both lakes during this time period. The amount of increase in LSWT values was about 2.2 °C for Burdur Lake, while about 1.3 °C for Egirdir Lake.

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DETECTION AGRICULTURE DEGRADATION FOR THE SOUTH OF BAGHDAD CITY USING REMOTE SENSING DATA FOR YEARS 2010-2019

MINAR International Journal of Applied Sciences and Technology ◽

10.47832/2717-8234.4-2.6 ◽

2020 ◽

pp. 57-67

Author(s):

Taif Adil DHAMIN ◽

Ebtesam F. KHANJER ◽

Fouad K. MASHEE

Keyword(s):

Remote Sensing ◽

Land Degradation ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Remote Sensing Data ◽

Military Operations ◽

The South ◽

Water Index ◽

Rs And Gis ◽

Landsat Satellite

Recently, the develop of the science of remote sensing enabled humanity to achieve the accuracy and wide coverage for different natural phenomena, disasters and applications (such as desertification, rainstorms, floods, fires, sweeping torrents, urban planning, and even in military). The main aim of this study is monitoring, highlighting and assessing maps for the degradation of agriculture in the south areas of Baghdad governorate (Al-Rasheed, Al-Yusufiyah, Al-Mahmudiyah, Al-Latifiyah, and Al-Madaen). Based to several factors, including the economic, social and military operations, the area had suffer the lands degradation which led to agriculture retreating. Remote sensing and Geographic information system (GIS) was applied, using ArcGIS 10.4.1 to process, manage, and analysis datasets, beside field verification to estimate the severity assessment of a computerized land degradation. Two satellites were adapted Landsat5 TM+ and Landsat8 OLI/TIRS imageries to assess the extent of land degradation for the study area during the years (5th May 2010 and 2nd May 2019). Two indices used in this research are: The Normalized Difference Vegetation Index “NDVI”, and The Normalized Differential Water Index “NDWI”. The results showed that there is a clear spatial reduction in both NDVI and NDWI, where the NDVI reduced from 2461082400 m2 to 1552698000 m2, accounting for 89.67 and 56.57 percent, respectively, while the NDWI reduced from 14166000 m2 to 12053700 m2, accounting for 0.52, and 0.44 percent, respectively. Keywords: Agriculture Degradation, RS And GIS Techniques, Landsat Satellite Imagery, NDVI And NDWI.

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Development of a New Phenology Algorithm for Fine Mapping of Cropping Intensity in Complex Planting Areas Using Sentinel-2 and Google Earth Engine

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10090587 ◽

2021 ◽

Vol 10 (9) ◽

pp. 587

Author(s):

Yan Guo ◽

Haoming Xia ◽

Li Pan ◽

Xiaoyang Zhao ◽

Rumeng Li ◽

...

Keyword(s):

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Growth Cycle ◽

Google Earth ◽

Henan Province ◽

Cropping Intensity ◽

Water Index ◽

Google Earth Engine ◽

Sentinel 2

Cropping intensity is a key indicator for evaluating grain production and intensive use of cropland. Timely and accurately monitoring of cropping intensity is of great significance for ensuring national food security and improving the level of national land management. In this study, we used all Sentinel-2 images on the Google Earth Engine cloud platform, and constructed an improved peak point detection method to extract the cropping intensity of a heterogeneous planting area combined with crop phenology. The crop growth cycle profiles were extracted from the multi-temporal normalized difference vegetation index (NDVI) and land surface water index (LSWI) datasets. Results show that by 2020, the area of single cropping, double cropping, and triple cropping in the Henan Province are 52,236.9 km2, 74,334.1 km2, and 1927.1 km2, respectively; the corresponding producer accuracies are 86.12%, 93.72%, and 91.41%, respectively; the corresponding user accuracies are 88.99%, 92.29%, and 71.26%, respectively. The overall accuracy is 90.95%, and the Kappa coefficient is 0.81. Using the sown area in the statistical yearbook data of cities in the Henan Province to verify the extraction results of this paper, the R2 is 0.9717, and the root mean square error is 1715.9 km2. This study shows that using all the Sentinel-2 data, the phenology algorithm, and cloud computing technology has great potential in producing a high spatio-temporal resolution dataset for crop remote sensing monitoring and agricultural policymaking in complex planting areas.

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Time-Series Assessment of Camp-Type Artisanal and Small-Scale Gold Mining Sectors with Large Influxes of Miners Using LANDSAT Imagery

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18189441 ◽

2021 ◽

Vol 18 (18) ◽

pp. 9441

Author(s):

Satomi Kimijima ◽

Masayuki Sakakibara ◽

Masahiko Nagai ◽

Nurfitri Gafur

Keyword(s):

Time Series ◽

Gold Mining ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat Imagery ◽

Market Price ◽

Fold Increase ◽

Google Earth ◽

Small Scale ◽

Field Investigations

Mining sites development have had a significant impact on local socioeconomic conditions, the environment, and sustainability. However, the transformation of camp-type artisanal and small-scale gold mining (ASGM) sites with large influxes of miners from different regions has not been properly evaluated, owing to the closed nature of the ASGM sector. Here, we use remote sensing imagery and field investigations to assess ASGM sites with large influxes of miners living in mining camps in Bone Bolango Regency, Gorontalo Province, Indonesia, in 1995–2020. Built-up areas were identified as indicators of transformation of camp-type ASGM sites, using the Normalized Difference Vegetation Index, from the time series of images obtained using Google Earth Engine, then correlated with the prevalent gold market price. An 18.6-fold increase in built-up areas in mining camps was observed in 2020 compared with 1995, which correlated with increases in local gold prices. Field investigations showed that miner influx also increased after increases in gold prices. These findings extend our understanding of the rate and scale of development in the closed ASGM sector and the driving factors behind these changes. Our results provide significant insight into the potential rates and levels of socio-environmental pollution at local and community levels.

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Developing land-state maps of Tram Chim National Park in Vietnam based on monitoring results

Geodesy and Cartography ◽

10.22389/0016-7126-2020-963-9-53-64 ◽

2020 ◽

Vol 963 (9) ◽

pp. 53-64

Author(s):

V.F. Kovyazin ◽

Thi Lan Anh Dang ◽

Viet Hung Dang

Keyword(s):

National Park ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Likelihood Method ◽

Wetland Area ◽

Water Index ◽

Effi Ciency ◽

Normalized Difference Water Index ◽

Specially Protected Natural Areas ◽

Protected Natural Areas

Tram Chim National Park in Southern Vietnam is a wetland area included in the system of specially protected natural areas (SPNA). For the purposes of land monitoring, we studied Landsat-5 and Sentinel-2B images obtained in 1991, 2006 and 2019. The methods of normalized difference vegetation index (NDVI) and water objects – normalized difference water index (NDWI) were used to estimate the vegetation in National Park. The allocated land is classifi ed by the maximum likelihood method in ENVI 5.3 into categories. For each image, a statistical analysis of the land after classifi cation was performed. Between 1991 and 2019, land changes occurred in about 57 % of the Tram Chim National Park total area. As a result, the wetland area has signifi cantly reduced there due to climate change. However, the area of Melaleuca forests in Tram Chim National Park has increased due to the effi ciency of reforestation in protected areas. Melaleuca forests are also being restored.

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An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

Remote Sensing ◽

10.3390/rs13040766 ◽

2021 ◽

Vol 13 (4) ◽

pp. 766

Author(s):

Yuanmao Zheng ◽

Qiang Zhou ◽

Yuanrong He ◽

Cuiping Wang ◽

Xiaorong Wang ◽

...

Keyword(s):

Urban Development ◽

Urban Areas ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Development Planning ◽

Urban Land ◽

Sustainable Urban Development ◽

Land Use Patterns ◽

Water Index ◽

Nighttime Light

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

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Modeling of Durum Wheat Yield Based on Sentinel-2 Imagery

Agronomy ◽

10.3390/agronomy11081486 ◽

2021 ◽

Vol 11 (8) ◽

pp. 1486

Author(s):

Chris Cavalaris ◽

Sofia Megoudi ◽

Maria Maxouri ◽

Konstantinos Anatolitis ◽

Marios Sifakis ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Vegetation Indices ◽

Model Development ◽

Wheat Yield ◽

Growth Period ◽

Yield Data ◽

Water Index ◽

Normalized Difference Water Index ◽

Sentinel 2

In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.

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Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

Anais da Academia Brasileira de Ciências ◽

10.1590/s0001-37652012005000018 ◽

2012 ◽

Vol 84 (2) ◽

pp. 263-274 ◽

Cited By ~ 3

Author(s):

Fábio M. Breunig ◽

Lênio S. Galvão ◽

Antônio R. Formaggio ◽

José C.N. Epiphanio

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Vegetation Indices ◽

Constant Factor ◽

The Other ◽

Large Field ◽

Phenological Stages ◽

Water Index ◽

Growing Seasons ◽

Moderate Resolution Imaging Spectroradiometer

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

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STUDY ON SPATIAL-TEMPORAL VARIATION OF HONG LAKE BASED ON VIIRS AND MODIS IMAGES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w7-797-2017 ◽

2017 ◽

Vol XLII-2/W7 ◽

pp. 797-802

Author(s):

C. Li ◽

Y. Zhong ◽

W. Zhang

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Infrared Imaging ◽

Spatial Location ◽

Water Extraction ◽

Water Index ◽

Average Area ◽

Flood Season ◽

Modis Image ◽

Lake Waters

Hong Lake is the largest lake in Hubei Province. With the increase of Hong Lake economic activity, the area, spatial location and shape of Hong Lake have changed greatly in the past. In this paper, we used the images, which is from the visible infrared imaging radiometer (VIIRS). First, we selected the images of Hong Lake waters on December 6, 2016 and December 26, 2015. Then we extracted the water bodies by the single-band method, spectral relationship method, normalized difference water index (NDWI) were used, and the effect-s were compared. Second, the images of Hong Lake waters in summer and winter were selected from 2012 to 2016, respectively. Last, The NDWI was used to extract the water body and compared with the MODIS image extraction effect in the same period. As a result of the vegetation around Hong Lake, the water is extracted by NDWI and normalized difference vegetation index (NDVI). It is found that for the VIIRS image, the NDWI is the best in the water extraction of Hong Lake. The NDVI + NDWI method is beneficial to the extraction of water covered with aquatic plants. VIIRS image extraction is better than MODIS image. In addition, from the study of VIIRS and MODIS to Hong Lake waters in the five years of water extraction and area calculation, 2012&ndash;2016 period, Hong Lake’s average area of 348.213&thinsp;km2 in flood season, in dry season average area of 349.163&thinsp;km2. The largest area for the 2012 flood season 389.751&thinsp;km2, the smallest area of 2016 flood season 306.177&thinsp;km2. Overall, Hong Lake’s area changes little.

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AEROSPACE MONITORING OF THE FOREST ECOSYSTEM DYNAMICS WITHIN THE TERRITORY OF VRACHANSKI BALKAN NATURE PARK

10.32006/eeep.2018.2.4146 ◽

2018 ◽

pp. 41-46

Author(s):

Adlin Dancheva

Keyword(s):

Remote Sensing ◽

Forest Ecosystem ◽

Vegetation Index ◽

Forest Ecosystems ◽

Normalized Difference Vegetation Index ◽

Remote Sensing And Gis ◽

Ecosystem Dynamics ◽

Anthropogenic Pressure ◽

Water Index ◽

Nature Park

In this paper the application of Remote Sensing and GIS as a means of performing aero – space monitoring of forest ecosystems dynamics is being considered. The purpose of this work is to create a model for monitoring the dynamic of forest ecosystems, based on Remote Sensing and GIS. The results of eco-monitoring can be used to update plans and policies for forest ecosystem management. The territory of Vrachanski Balkan Nature park was chosen as the subject of research as there is a certain anthropogenic pressure there. The results presented are obtained by spatial-time analysis of certain aerospace data indices. To carry out the study optical satellite images were used, on the basics of which three indices were calculated: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Greenness Index (NDGI). A comparative analysis has been created and results of the degree of correlation between the different indices are presented, as well as indicators from the different test areas and related changes in the individual points in time. The results of the survey aim to assess the dynamics and condition of the forest vegetation on the territory of Vrachanski Balkan Nature park and can be utilised in activities related to monitoring, mapping and forest management.

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