Assessing the impact of N-fertilization on biochemical composition and biomass of a Douglas-fir canopy—A remote sensing approach

2012 ◽  
Vol 153 ◽  
pp. 124-133 ◽  
Author(s):  
Thomas Hilker ◽  
Lucie Lepine ◽  
Nicholas C. Coops ◽  
Rachhpal S. Jassal ◽  
T. Andrew Black ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Biochemical Composition ◽  
N Fertilization ◽  
Douglas Fir ◽  
The Impact

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals Remote Sensing to Study Mangrove Fragmentation and Its Impacts on Leaf Area Index and Gross Primary Productivity in the South of Peninsular Malaysia

2021 ◽  
Vol 13 (8) ◽  
pp. 1427
Author(s):  
Kasturi Devi Kanniah ◽  
Chuen Siang Kang ◽  
Sahadev Sharma ◽  
A. Aldrie Amir
Keyword(s):  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Primary Productivity ◽  
Peninsular Malaysia ◽  
Area Index ◽  
Mangrove Area ◽  
The Mean ◽  
Shape Complexity ◽  
The Impact

Mangrove is classified as an important ecosystem along the shorelines of tropical and subtropical landmasses, which are being degraded at an alarming rate despite numerous international treaties having been agreed. Iskandar Malaysia (IM) is a fast-growing economic region in southern Peninsular Malaysia, where three Ramsar Sites are located. Since the beginning of the 21st century (2000–2019), a total loss of 2907.29 ha of mangrove area has been estimated based on medium-high resolution remote sensing data. This corresponds to an annual loss rate of 1.12%, which is higher than the world mangrove depletion rate. The causes of mangrove loss were identified as land conversion to urban, plantations, and aquaculture activities, where large mangrove areas were shattered into many smaller patches. Fragmentation analysis over the mangrove area shows a reduction in the mean patch size (from 105 ha to 27 ha) and an increase in the number of mangrove patches (130 to 402), edge, and shape complexity, where smaller and isolated mangrove patches were found to be related to the rapid development of IM region. The Moderate Resolution Imaging Spectro-radiometer (MODIS) Leaf Area Index (LAI) and Gross Primary Productivity (GPP) products were used to inspect the impact of fragmentation on the mangrove ecosystem process. The mean LAI and GPP of mangrove areas that had not undergone any land cover changes over the years showed an increase from 3.03 to 3.55 (LAI) and 5.81 g C m−2 to 6.73 g C m−2 (GPP), highlighting the ability of the mangrove forest to assimilate CO2 when it is not disturbed. Similarly, GPP also increased over the gained areas (from 1.88 g C m−2 to 2.78 g C m−2). Meanwhile, areas that lost mangroves, but replaced them with oil palm, had decreased mean LAI from 2.99 to 2.62. In fragmented mangrove patches an increase in GPP was recorded, and this could be due to the smaller patches (<9 ha) and their edge effects where abundance of solar radiation along the edges of the patches may increase productivity. The impact on GPP due to fragmentation is found to rely on the type of land transformation and patch characteristics (size, edge, and shape complexity). The preservation of mangrove forests in a rapidly developing region such as IM is vital to ensure ecosystem, ecology, environment, and biodiversity conservation, in addition to providing economical revenue and supporting human activities.

scholarly journals Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3982
Author(s):  
Giacomo Lazzeri ◽  
William Frodella ◽  
Guglielmo Rossi ◽  
Sandro Moretti
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Fire Severity ◽  
Experimental Methodology ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
The Impact ◽  
Sentinel 2

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

Assessing the impact of agricultural field traffic on corn grain yield using remote sensing and machine learning

2021 ◽  
Vol 208 ◽  
pp. 104880
Author(s):  
Sami Khanal ◽  
Andrew Klopfenstein ◽  
Kushal KC ◽  
Venkatesh Ramarao ◽  
John Fulton ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Grain Yield ◽  
Agricultural Field ◽  
The Impact ◽  
Corn Grain ◽  
Corn Grain Yield

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.

Regional characterisation of soil properties by combining soil science and hyperspectral and thermal remote sensing: A technical overview of lab and field remote sensing methods

2021 ◽  
Author(s):  
Richard Mommertz ◽  
Lars Konen ◽  
Martin Schodlok
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Regional Scale ◽  
Arable Land ◽  
Soil Mapping ◽  
Soil Science ◽  
Near Surface ◽  
Soil Parameter ◽  
The Impact ◽  
Parameter Retrieval

&lt;p&gt;Soil is one of the world&amp;#8217;s most important natural resources for human livelihood as it provides food and clean water. Therefore, its preservation is of huge importance. For this purpose, a proficient regional database on soil properties is needed. The project &amp;#8220;ReCharBo&amp;#8221; (Regional Characterisation of Soil Properties) has the objective to combine remote sensing, geophysical and pedological methods to determine soil characteristics on a regional scale. Its aim is to characterise soils non-invasive, time and cost efficient and with a minimal number of soil samples to calibrate the measurements. Konen et al. (2021) give detailed information on the research concept and first field results in a presentation in the session &amp;#8220;SSS10.3 Digital Soil Mapping and Assessment&amp;#8221;. Hyperspectral remote sensing is a powerful and well known technique to characterise near surface soil properties. Depending on the sensor technology and the data quality, a wide variety of soil properties can be derived with remotely sensed data (Chabrillat et al. 2019, Stenberg et al. 2010). The project aims to investigate the effects of up and downscaling, namely which detail of information is preserved on a regional scale and how a change in scales affects the analysis algorithms and the possibility to retrieve valid soil parameter information. Thus, e.g. laboratory and field spectroscopy are applied to gain information of samples and fieldspots, respectively. Various UAV-based sensors, e.g. thermal &amp; hyperspectral sensors, are applied to study soil properties of arable land in different study areas at field scale. Finally, airborne (helicopter) hyperspectral data will cover the regional scale. Additionally forthcoming spaceborne hyperspectral satellite data (e.g. Prisma, EnMAP, Sentinel-CHIME) are a promising outlook to gain detailed regional soil information. In this context it will be discussed how the multisensor data acquisition is best managed to optimise soil parameter retrieval. Sensor specific properties regarding time and date of acquisition as well as weather/atmospheric conditions are outlined. The presentation addresses and discusses the impact of a multisensor and multiscale remote sensing data collection regarding the results on soil parameter retrieval.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References&lt;/p&gt;&lt;p&gt;Chabrillat, S., Ben-Dor, E. Cierniewski, J., Gomez, C., Schmid, T. &amp; van Wesemael, B. (2019): Imaging Spectroscopy for Soil Mapping and Monitoring. Surveys in Geophysics 40:361&amp;#8211;399. https://doi.org/10.1007/s10712-019-09524-0&lt;/p&gt;&lt;p&gt;Stenberg, B., Viscarra Rossel, R. A., Mounem Mouazen, A. &amp; Wetterlind, J. (2010): Visible and Near Infrared Spectroscopy in Soil Science. In: Donald L. Sparks (editor): Advances in Agronomy. Vol. 107. Academic Press:163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7&lt;/p&gt;

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