scholarly journals No-till identification by crop residues on the soil surface using the multi-temporal integral index minNDTI

2021 ◽  
Vol 4 (46) ◽  
pp. 1-1
Author(s):  
Alexander Saakian ◽  
◽  
Keyword(s):  
Satellite Images ◽  
Crop Residues ◽  
Soil Surface ◽  
Field Work ◽  
Google Earth ◽  
No Till ◽  
Multi Temporal ◽  
Time Periods ◽  
Direct Sowing ◽  
Sentinel 2

The study analyzed the possibility of using the multi-temporal spectral index minNDTI to identify farms using no-till. Using the Google earth engine platform, satellite images of the Sentinel 2 system were obtained, processed and analyzed for two time periods. Based on the data obtained, NDTI images were constructed for periods of fieldwork, as well as multi-temporal minNDTI images. As a result of the statistical analysis, significant differences were found between the NDTI values of the samples from the plowing and no-till options for two time periods in which the field work was carried out and between the multi-time values for two years of research. Based on the dynamics of the values of the multi-temporal index minNDTI, a map of the probability of assigning fields to direct sowing was constructed. Ключевые слова: NO-TILL, CROP RESIDUES, GIS, REMOTE SENSING, SPECTRAL INDICES, NDTI

scholarly journals Вплив «нульового» і традиційного обробітків ґрунту на кількість дощових черв’яків у посівах ячменю ярого Правобережного Лісостепу України

2016 ◽  
pp. 25-27
Author(s):  
С. П. Танчик ◽  
О. М. Одарченко
Keyword(s):  
Crop Residues ◽  
Spring Barley ◽  
Soil Surface ◽  
Conventional Tillage ◽  
Positive Influence ◽  
Forest Steppe ◽  
No Till ◽  
Direct Sowing

Досліджено вплив «нульового» і традиційного обробітків на кількість дощових черв’яків в орному шарі чорнозему типового у полі ячменю ярого Правобережного Лісостепу України. Встановлено, що відсутність обробітку ґрунту та накопичення пожнивних решток на його поверхні у варіанті «прямого» висіву позитивно впливали на розвиток популяції дощових черв’яків, що призводило до збільшення їх кількості у 2,6 разів у порівнянні з полицевим обробітком. Виявлено, що за традиційного обробітку від сівби до збирання ячменю ярого відбувалося зменшення дощових черв’яків більше ніж у 9 разів, у той час як за нульового обробітку даний показник зменшився у 2,2 рази. The effect of No-till and conventional tillage on the number of earthworms in the plow layer of typical black earth in spring barley of Right-Bank Forest-Steppe was researched. It was established that the absence of tillage and crop residues accumulation on soil surface under «direct» sowing had a positive influence on the population of earthworms, which led to increase in their number by 2,6 times compared to plow. In plowing variant the amount of earthworms was reducing from sowing to harvesting of spring barley more than 9 times, while in case of No-till it decreased in 2,2 times.

scholarly journals The use of index images for decoding the vegetation cover of inner mountain Dagestan, Russia

2021 ◽  
Vol 15 (4) ◽  
pp. 126-136
Author(s):  
R. T. Radzhabova ◽  
N. A. Alekseenko ◽  
B. M. Kuramagomedov ◽  
Z. Sh. Tazhudinova ◽  
Z. M. Sultanov
Keyword(s):  
Vegetation Cover ◽  
Satellite Images ◽  
Spatial Information ◽  
High Spatial Resolution ◽  
Imaging System ◽  
Field Research ◽  
Digital Processing ◽  
Google Earth ◽  
Multi Temporal ◽  
Sentinel 2

Aim. Selection and analysis of index images suitable for deciphering the vegetation cover in the conditions of inner mountain Dagestan.Methods. The study was carried out on the basis of multi-temporal satellite images of high spatial resolution, obtained by the imaging system of the Sentinel-2 series satellite, using methods of digital processing of geoimages. Processing was carried out using the capabilities of the Google Earth Engine geoservice.Results. Multi-temporal index images were obtained for the territory of inner mountain Dagestan. The time series of seasonal changes in the indices (NDVI, SAVI, EVI) were analyzed, making it possible to reveal the phenological patterns of vegetation and to map the vegetation cover on this basis. Schemes for decoding vegetation have been created by which areas are distinguished according to the following characteristics: devoid of vegetation, herbaceous vegetation of varying degrees of density or woody (deciduous and coniferous).Conclusion. When studying vegetation cover using index images in a range of natural conditions, it is necessary to take into account the natural features of the territory, as well using additional sources of spatial information including field research methods.

ANALISIS TEMPORAL PERUBAHAN HUTAN MANGROVE MENGGUNAKAN CITRA SATELIT SENTINEL-2 (Studi Kasus di Pulau Tanakeke, Kabupaten Takalar)

2021 ◽  
pp. 777
Author(s):  
Andi Tenri Waru ◽  
Athar Abdurrahman Bayanuddin ◽  
Ferman Setia Nugroho ◽  
Nita Rukminasari
Keyword(s):  
Random Forest ◽  
Google Earth ◽  
Multi Temporal ◽  
Google Earth Engine ◽  
Sentinel 2

Pulau Tanakeke merupakan salah satu pulau dengan hutan mangrove yang luas di pesisir Sulawesi Selatan. Hutan mangrove ini menjadi ekosistem penting bagi masyarakat sekitar karena nilai ekologi maupun ekonominya. Namun, dalam kurun waktu sekitar tahun 1980-2000, keberadaan mangrove tersebut terancam oleh perubahan penggunaan lahan dan juga pemanfaatan yang berlebihan. Penelitian ini bertujuan untuk menganalisis perubahan temporal luas dan tingkat kerapatan hutan mangrove di Pulau Tanakeke antara tahun 2016 dan 2019. Metode analisis perubahan luasan hutan mangrove menggunakan data citra satelit Sentinel-2 multi temporal berdasarkan hasil klasifikasi hutan mangrove dengan menggunakan random forest pada platform Google Earth Engine. Akurasi keseluruhan hasil klasifikasi hutan mangrove tahun 2016 dan 2019 sebesar 91% dan 98%. Berdasarkan hasil analisis spasial diperoleh perubahan penurunan luasan mangrove yang signifikan dari 800,21 ha menjadi 640,15 ha. Kerapatan mangrove di Pulau Tanakeke sebagian besar tergolong kategori dalam kerapatan tinggi.

Heavy metal-induced stress in rice crops detected using multi-temporal Sentinel-2 satellite images

2018 ◽  
Vol 637-638 ◽  
pp. 18-29 ◽  
Author(s):  
Meiling Liu ◽  
Tiejun Wang ◽  
Andrew K. Skidmore ◽  
Xiangnan Liu
Keyword(s):  
Heavy Metal ◽  
Satellite Images ◽  
Induced Stress ◽  
Multi Temporal ◽  
Sentinel 2

A new approach for biocrust and vegetation monitoring in drylands using multi-temporal Sentinel-2 images

2019 ◽  
Vol 43 (4) ◽  
pp. 496-520 ◽  
Author(s):  
Cinzia Panigada ◽  
Giulia Tagliabue ◽  
Eli Zaady ◽  
Offer Rozenstein ◽  
Roberto Garzonio ◽  
...  
Keyword(s):  
Vascular Plant ◽  
Temporal Distribution ◽  
Soil Surface ◽  
Absorption Feature ◽  
Arid Environments ◽  
Vegetation Monitoring ◽  
Rainfall Gradient ◽  
The North ◽  
Multi Temporal ◽  
Sentinel 2

Drylands, one of the planet’s largest terrestrial biomes, are suggested to be greatly threatened by climate change. Drylands are usually sparsely vegetated, and biological soil crusts (biocrusts) – that is, soil surface communities of cyanobacteria, mosses and/or lichens – can cover up to 70% of dryland cover. As they control key ecosystem processes, monitoring their spatial and temporal distribution can provide highly valuable information. In this study, we examine the potential of European Space Agency’s (ESA) Sentinel-2 (S2) data to characterize the spatial and temporal development of biocrust and vascular plant greening along a rainfall gradient of the Negev Desert (Israel). First, the chlorophyll a absorption feature in the red region (CRred) was identified as the index mostly sensitive to changes in biocrust greening but minimally affected by changes in soil moisture. This index was then computed on the S2 images and enabled monitoring the phenological dynamics of different dryland vegetation components from August 2015 to August 2017. The analysis of multi-temporal S2 images allowed us to successfully track the biocrust greening within 15 days from the first seasonal rain events in the north of Negev, and to identify the maximum development of annual vascular plants and greening of perennial ones. These results show potential for monitoring arid and semi-arid environments using the newly available S2 images, allowing new insights into dryland vegetation dynamics.

scholarly journals Mapping Winter Wheat with Combinations of Temporally Aggregated Sentinel-2 and Landsat-8 Data in Shandong Province, China

2020 ◽  
Vol 12 (12) ◽  
pp. 2065 ◽  
Author(s):  
Feng Xu ◽  
Zhaofu Li ◽  
Shuyu Zhang ◽  
Naitao Huang ◽  
Zongyao Quan ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Google Earth ◽  
Shandong Province ◽  
Sensor Data ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Multi Temporal ◽  
Wheat Development ◽  
Development Phases ◽  
Sentinel 2

Winter wheat is one of the major cereal crops in China. The spatial distribution of winter wheat planting areas is closely related to food security; however, mapping winter wheat with time-series finer spatial resolution satellite images across large areas is challenging. This paper explores the potential of combining temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data available via the Google Earth Engine (GEE) platform for mapping winter wheat in Shandong Province, China. First, six phenological median composites of Landsat-8 OLI and Sentinel-2 MSI reflectance measures were generated by a temporal aggregation technique according to the winter wheat phenological calendar, which covered seedling, tillering, over-wintering, reviving, jointing-heading and maturing phases, respectively. Then, Random Forest (RF) classifier was used to classify multi-temporal composites but also mono-temporal winter wheat development phases and mono-sensor data. The results showed that winter wheat could be classified with an overall accuracy of 93.4% and F1 measure (the harmonic mean of producer’s and user’s accuracy) of 0.97 with temporally aggregated Landsat-8 and Sentinel-2 data were combined. As our results also revealed, it was always good to classify multi-temporal images compared to mono-temporal imagery (the overall accuracy dropped from 93.4% to as low as 76.4%). It was also good to classify Landsat-8 OLI and Sentinel-2 MSI imagery combined instead of classifying them individually. The analysis showed among the mono-temporal winter wheat development phases that the maturing phase’s and reviving phase’s data were more important than the data for other mono-temporal winter wheat development phases. In sum, this study confirmed the importance of using temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data combined and identified key winter wheat development phases for accurate winter wheat classification. These results can be useful to benefit on freely available optical satellite data (Landsat-8 OLI and Sentinel-2 MSI) and prioritize key winter wheat development phases for accurate mapping winter wheat planting areas across China and elsewhere.

The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review

2021 ◽  
Author(s):  
Crismeire Isbaex ◽  
Ana Margarida Coelho
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Forest Biomass ◽  
Local Scale ◽  
Google Earth ◽  
Biomass Estimation ◽  
Promising Tool ◽  
Google Earth Engine ◽  
Sentinel 2

Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images is a challenge given the diversity of sensors available and the heterogeneity of forests. Copernicus program served by the Sentinel satellites family and the Google Earth Engine (GEE) platform, both with free and open services accessible to its users, present a good approach for mapping vegetation and estimate forest biomass on a global, regional, or local scale, periodically and in a repeated way. The Sentinel-2 (S2) systematically acquires optical imagery and provides global monitoring data with high spatial resolution (10–60 m) images. Given the novelty of information on the use of S2 data, this chapter presents a review on LCLU maps and forest above-ground biomass (AGB) estimates, in addition to exploring the efficiency of using the GEE platform. The Sentinel data have great potential for studies on LCLU classification and forest biomass estimates. The GEE platform is a promising tool for executing complex workflows of satellite data processing.

scholarly journals Multi-Temporal Change Detection Analysis of Vertical Sprawl over Limassol City Centre and Amathus Archaeological Site in Cyprus during 2015–2020 Using the Sentinel-1 Sensor and the Google Earth Engine Platform

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1884
Author(s):  
Athos Agapiou
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Archaeological Site ◽  
Google Earth ◽  
City Centre ◽  
Time Interval ◽  
High Resolution Satellite Images ◽  
Multi Temporal ◽  
Google Earth Engine ◽  
The City

Urban sprawl can negatively impact the archaeological record of an area. In order to study the urbanisation process and its patterns, satellite images were used in the past to identify land-use changes and detect individual buildings and constructions. However, this approach involves the acquisition of high-resolution satellite images, the cost of which is increases according to the size of the area under study, as well as the time interval of the analysis. In this paper, we implemented a quick, automatic and low-cost exploration of large areas, for addressing this purpose, aiming to provide at a medium resolution of an overview of the landscape changes. This study focuses on using radar Sentinel-1 images to monitor and detect multi-temporal changes during the period 2015–2020 in Limassol, Cyprus. In addition, the big data cloud platform, Google Earth Engine, was used to process the data. Three different change detection methods were implemented in this platform as follow: (a) vertical transmit, vertical receive (VV) and vertical transmit, horizontal receive (VH) polarisations pseudo-colour composites; (b) the Rapid and Easy Change Detection in Radar Time-Series by Variation Coefficient (REACTIV) Google Earth Engine algorithm; and (c) a multi-temporal Wishart-based change detection algorithm. The overall findings are presented for the wider area of the Limassol city, with special focus on the archaeological site of “Amathus” and the city centre of Limassol. For validation purposes, satellite images from the multi-temporal archive from the Google Earth platform were used. The methods mentioned above were able to capture the urbanization process of the city that has been initiated during this period due to recent large construction projects.

scholarly journals Carbon balance and crop residue management in dynamic equilibrium under a no-till system in Campos Gerais

2012 ◽  
Vol 36 (5) ◽  
pp. 1583-1590 ◽  
Author(s):  
Ademir de Oliveira Ferreira ◽  
João Carlos de Moraes Sá ◽  
Mônica Gabrielle Harms ◽  
Simone Miara ◽  
Clever Briedis ◽  
...  
Keyword(s):  
Carbon Balance ◽  
Crop Residues ◽  
Dynamic Equilibrium ◽  
Soil Surface ◽  
C Sequestration ◽  
Residue Management ◽  
Minimum Amount ◽  
No Till ◽  
Sequestration Rate

The adoption of no-tillage systems (NT) and the maintenance of crop residues on the soil surface result in the long-term increase of carbon (C) in the system, promoting C sequestration and reducing C-CO2 emissions to the atmosphere. The purpose of this study was to evaluate the C sequestration rate and the minimum amount of crop residues required to maintain the dynamic C equilibrium (dC/dt = 0) of two soils (Typic Hapludox) with different textural classes. The experiment was arranged in a 2 x 2 x 2 randomized block factorial design. The following factors were analyzed: (a) two soil types: Typic Hapludox (Oxisol) with medium texture (LVTM) and Oxisol with clay texture (LVTA), (b) two sampling layers (0-5 and 5-20 cm), and (c) two sampling periods (P1 - October 2007; P2 - September 2008). Samples were collected from fields under a long-term (20 years) NT system with the following crop rotations: wheat/soybean/black oat + vetch/maize (LVTM) and wheat/maize/black oat + vetch/soybean (LVTA). The annual C sequestration rates were 0.83 and 0.76 Mg ha-1 for LVTM and LVTA, respectively. The estimates of the minimum amount of crop residues required to maintain a dynamic equilibrium (dC/dt = 0) were 7.13 and 6.53 Mg ha-1 year-1 for LVTM and LVTA, respectively. The C conversion rate in both studied soils was lower than that reported in other studies in the region, resulting in a greater amount of crop residues left on the soil surface.

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