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.

Jamaican limestone forests: floristics, structure and environment of three examples along a rainfall gradient

1988 ◽  
Vol 4 (2) ◽  
pp. 121-156 ◽  
Author(s):  
D. L. Kelly ◽  
E. V. J. Tanner ◽  
V. Kapos ◽  
T. A. Dickinson ◽  
G. A. Goodfriend ◽  
...  
Keyword(s):  
Vascular Plant ◽  
Leaf Size ◽  
Evergreen Forest ◽  
Rainfall Gradient ◽  
Neotropical Forests ◽  
Montane Rain Forest ◽  
North East ◽  
The North ◽  
Species Area ◽  
C 50

ABSTRACTWe describe forests from three areas of Jamaica, all on White Limestone but with markedly different rainfall regimes. The areas are Hog House Hill in the north-east with lower montane rain forest at c. 450 m altitude with a rainfall of c. 4000 mm yr−1; Broom Hall in the centre of the island with evergreen seasonal forest at c. 670 m altitude and with a rainfall of c. 1600 mm yr−1 and a marked dry season; and Round Hill near the south coast with dry semi-evergreen forest at c. 300 m altitude with an irregularly distributed rainfall of c. 1000 mm yr−1. Species lists were made from c. 180 ha at Hog House Hill, c. 5 ha at Broom Hall and c. 50 ha at Round Hill, and detailed inventories made of five sample sites of c. 1000 m2, two at Hog House Hill, one at Broom Hall and two at Round Hill.At Hog House Hill we listed 280 vascular plant species, including 118 species of trees and larger shrubs; at Broom Hall 247 and 135; at Round Hill 129 and 81. Species-area and species-individuals curves confirm that Broom Hall was richer in tree species than Hog House Hill. The wetter forests contain high proportions of species endemic to Jamaica: 40% of the total flora at Hog House Hill and 36% at Broom Hall. Canopy height decreased from c. 26–28 m at Hog House Hill to c. 13–24 m at Broom Hall to c. 8–15 m at Round Hill. Predominant leaf size decreased from mesophyll at Hog House Hill to notophyll at Broom Hall to microphyll at Round Hill.Compared with forests on other Caribbean islands, the Jamaican forests appear to be as species-rich as any, but lower in stature than natural forest in Trinidad and Dominica. Continental Neotropical forests are both more species-rich and taller.

scholarly journals Multi-Temporal Sentinel-2 Data in Classification of Mountain Vegetation

2020 ◽  
Vol 12 (17) ◽  
pp. 2696 ◽  
Author(s):  
Martyna Wakulińska ◽  
Adriana Marcinkowska-Ochtyra
Keyword(s):  
National Parks ◽  
Vegetation Indices ◽  
European Space Agency ◽  
Principal Component ◽  
Support Vector ◽  
Electromagnetic Spectrum ◽  
Vegetation Monitoring ◽  
Multi Temporal ◽  
Mountain Vegetation ◽  
Sentinel 2

The electromagnetic spectrum registered via satellite remote sensing methods became a popular data source that can enrich traditional methods of vegetation monitoring. The European Space Agency Sentinel-2 mission, thanks to its spatial (10–20 m) and spectral resolution (12 spectral bands registered in visible-, near-, and mid-infrared spectrum) and primarily its short revisit time (5 days), helps to provide reliable and accurate material for the identification of mountain vegetation. Using the support vector machines (SVM) algorithm and reference data (botanical map of non-forest vegetation, field survey data, and high spatial resolution images) it was possible to classify eight vegetation types of Giant Mountains: bogs and fens, deciduous shrub vegetation, forests, grasslands, heathlands, subalpine tall forbs, subalpine dwarf pine scrubs, and rock and scree vegetation. Additional variables such as principal component analysis (PCA) bands and selected vegetation indices were included in the best classified dataset. The results of the iterative classification, repeated 100 times, were assessed as approximately 80% median overall accuracy (OA) based on multi-temporal datasets composed of images acquired through the vegetation growing season (from late spring to early autumn 2018), better than using a single-date scene (70%–72% OA). Additional variables did not significantly improve the results, showing the importance of spectral and temporal information themselves. Our study confirms the possibility of fully available data for the identification of mountain vegetation for management purposes and protection within national parks.

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

In memory of Vera Antonovna Martynenko (1936-2018)

2018 ◽  
pp. 149-154
Keyword(s):  
Vascular Plants ◽  
Ussr Academy ◽  
Vascular Plant ◽  
Plant Cover ◽  
Komi Republic ◽  
Great Contribution ◽  
North East ◽  
The North ◽  
Natural Flora

Vera Antonovna Martynenko (17.02.1936–06.01.2018) — famous specialist in the field of studying vascular plant flora and vegetation of the Far North, the Honored worker of the Komi Republic (2006), The Komi Republic State Scientific Award winner (2000). She was born in the town Likhoslavl of the Kali­nin (Tver) region. In 1959, Vera Antonovna graduated from the faculty of soil and biology of the Leningrad State University and then moved to the Komi Branch of USSR Academy of Science (Syktyvkar). From 1969 to 1973 she passed correspondence postgraduate courses of the Komi Branch of USSR Academy of ­Science. In 1974, she received the degree of candidate of biology (PhD) by the theme «Comparative analysis of the boreal flora at the Northeast European USSR» in the Botanical Institute (St. Petersburg). In 1996, Vera Antonovna received the degree of doctor of biology in the Institute of plant and animal ecology (Ekaterinburg) «Flora of the northern and mid subzones of the taiga of the European North-East». The study and conservation of species and coenotical diversity of the plant world, namely the vascular plants flora of the Komi Republic and revealing its transformation under the anthropogenic influence, was in the field of V. A. Martynenko’ scientific interests. She made great contribution to the study of the Komi Republic meadow flora and the pool of medi­cinal plants. She performed inventorying and mapping the meadows of several agricultural enterprises of the Republic, revealed the species composition and places for harvesting medicinal plants and studied their productivity in the natural flora of the boreal zone. The results of her long-term studies were used for making the NPA system and the Red Book of the Komi Republic (1998 and 2009). Vera Antonovna participated in the research of the influence of placer gold mining and oil development on the natural ecosystems of the North, and developed the method of long-term monitoring of plant cover. Results of these works are of high practical value. V. A. Martynenko is an author and coauthor of more than 130 scientific publications. The most important jnes are «Flora of Northeast European USSR» (1974, 1976, and 1977), «Floristic composition of fodder lands of the Northeast Europe» (1989), «The forests of the Komi Republic» (1999), «Forestry of forest resources of the Komi Republic» (2000), «The list of flora of the Yugyd va national park» (2003), «The guide for vascular plants of the Syktyvkar and its vicinities» (2005), «Vascular plants of the Komi Republic» (2008), and «Resources of the natural flora of the Komi Republic» (2014). She also was an author of «Encyclopedia of the Komi Republic» (1997, 1999, and 2000), «Historical and cultural atlas of the Komi Republic» (1997), «Atlas of the Komi Republic» (2001, 2011). V. A. Martynenko made a great contribution to the development of the botanical investigations in the North. Since 1982, during more than 10 years, she was the head of the Department of the Institute of Biology. Three Ph. D. theses have been completed under her leadership. Many years, she worked actively in the Dissertation Council of the Institute of biology Komi Scientific Centre UrB RAS.  The death of Vera Antonovna Martynenko is a heavy and irretrievable loss for the staff of the Institute of Biology. The memory of Vera Antonovna will live in her numerous scientific works, the hearts of students and colleagues.

Assessment of Turbulent Processes in Lake Kinneret by the Two-Dimensional Reservoir Water Quality Model “Better”

1993 ◽  
Vol 27 (7-8) ◽  
pp. 381-385 ◽  
Author(s):  
Y. Oziransky ◽  
B. Shteinman
Keyword(s):  
Water Body ◽  
River Mouth ◽  
Temporal Distribution ◽  
Lake Kinneret ◽  
Toxic Substances ◽  
Two Dimensional ◽  
Quality Model ◽  
Reservoir Water ◽  
The North ◽  
Longitudinal Gradients

Data of high spatial and temporal resolution, and a special sampling program are essential for successful application of mathematical models designed to reproduce observed seasonal patterns of temperature, dissolved oxygen, nutrients, pH, and algal biomass for both vertical and longitudinal gradients in a water body. Lake Kinneret suspended solids are of great potential value for estimating transport, exposure to water body elements, and fate of many toxic substances. Therefore the distribution of admixtures in two longitudinal and five vertical segmentation schemes were examined with the two-dimensional water body quality box model “BETTER” (Bender et al, 1990). The transects were taken in the north-western part of Lake Kinneret close to the Jordan River mouth and the National Water Carrier (NWC) head pumping station. The outflow volumes were given according to regular sampling of natural speed of water outflow from different lake layers under calm conditions. Temporal distribution of mixing concentrations as well as turbulent diffusion horizontal coefficients due to the spatial distribution of turbulent scale were obtained during the model's run with the December 1991 data.

scholarly journals QVigourMap: A GIS Open Source Application for the Creation of Canopy Vigour Maps

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 952
Author(s):  
Lia Duarte ◽  
Ana Cláudia Teodoro ◽  
Joaquim J. Sousa ◽  
Luís Pádua
Keyword(s):  
Open Source ◽  
Precision Agriculture ◽  
Vegetation Indices ◽  
Data Interpretation ◽  
Vegetation Monitoring ◽  
Distribution Maps ◽  
Monitoring Process ◽  
Multi Temporal ◽  
The Creation ◽  
The Right

In a precision agriculture context, the amount of geospatial data available can be difficult to interpret in order to understand the crop variability within a given terrain parcel, raising the need for specific tools for data processing and analysis. This is the case for data acquired from Unmanned Aerial Vehicles (UAV), in which the high spatial resolution along with data from several spectral wavelengths makes data interpretation a complex process regarding vegetation monitoring. Vegetation Indices (VIs) are usually computed, helping in the vegetation monitoring process. However, a crop plot is generally composed of several non-crop elements, which can bias the data analysis and interpretation. By discarding non-crop data, it is possible to compute the vigour distribution for a specific crop within the area under analysis. This article presents QVigourMaps, a new open source application developed to generate useful outputs for precision agriculture purposes. The application was developed in the form of a QGIS plugin, allowing the creation of vigour maps, vegetation distribution maps and prescription maps based on the combination of different VIs and height information. Multi-temporal data from a vineyard plot and a maize field were used as case studies in order to demonstrate the potential and effectiveness of the QVigourMaps tool. The presented application can contribute to making the right management decisions by providing indicators of crop variability, and the outcomes can be used in the field to apply site-specific treatments according to the levels of vigour.

scholarly journals Some Peculiarities of Arable Soil Organic Matter Detection Using Optical Remote Sensing Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2313
Author(s):  
Elena Prudnikova ◽  
Igor Savin
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Spectral Reflectance ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Optical Remote Sensing ◽  
Test Field ◽  
Sensing Data ◽  
Sentinel 2

Optical remote sensing only provides information about the very thin surface layer of soil. Rainfall splash alters soil surface properties and its spectral reflectance. We analyzed the impact of rainfall on the success of soil organic matter (SOM) content (% by mass) detection and mapping based on optical remote sensing data. The subject of the study was the arable soils of a test field located in the Tula region (Russia), their spectral reflectance, and Sentinel-2 data. Our research demonstrated that rainfall negatively affects the accuracy of SOM predictions based on Sentinel-2 data. Depending on the average precipitation per day, the R2cv of models varied from 0.67 to 0.72, RMSEcv from 0.64 to 1.1% and RPIQ from 1.4 to 2.3. The incorporation of information on the soil surface state in the model resulted in an increase in accuracy of SOM content detection based on Sentinel-2 data: the R2cv of the models increased up to 0.78 to 0.84, the RMSEcv decreased to 0.61 to 0.71%, and the RPIQ increased to 2.1 to 2.4. Further studies are necessary to identify how the SOM content and composition of the soil surface change under the influence of rainfall for other soils, and to determine the relationships between rainfall-induced SOM changes and soil surface spectral reflectance.

scholarly journals Spatial–Temporal Distribution Variation of Ground-Level Ozone in China’s Pearl River Delta Metropolitan Region

2021 ◽  
Vol 18 (3) ◽  
pp. 872
Author(s):  
An Zhang ◽  
Jinhuang Lin ◽  
Wenhui Chen ◽  
Mingshui Lin ◽  
Chengcheng Lei
Keyword(s):  
Ozone Concentration ◽  
Pearl River Delta ◽  
Temporal Distribution ◽  
Ground Level ◽  
Metropolitan Region ◽  
Pearl River ◽  
Ozone Pollution ◽  
Ground Level Ozone ◽  
Ozone Concentrations ◽  
The North

Long-term exposure to ozone pollution will cause severe threats to residents’ physical and mental health. Ground-level ozone is the most severe air pollutant in China’s Pearl River Delta Metropolitan Region (PRD). It is of great significance to accurately reveal the spatial–temporal distribution characteristics of ozone pollution exposure patterns. We used the daily maximum 8-h ozone concentration data from PRD’s 55 air quality monitoring stations in 2015 as input data. We used six models of STK and ordinary kriging (OK) for the simulation of ozone concentration. Then we chose a better ozone pollution prediction model to reveal the ozone exposure characteristics of the PRD in 2015. The results show that the Bilonick model (BM) model had the highest simulation precision for ozone in the six models for spatial–temporal kriging (STK) interpolation, and the STK model’s simulation prediction results are significantly better than the OK model. The annual average ozone concentrations in the PRD during 2015 showed a high spatial variation in the north and east and low in the south and west. Ozone concentrations were relatively high in summer and autumn and low in winter and spring. The center of gravity of ozone concentrations tended to migrate to the north and west before moving to the south and then finally migrating to the east. The ozone’s spatial autocorrelation was significant and showed a significant positive correlation, mainly showing high-high clustering and low-low clustering. The type of clustering undergoes temporal migration and conversion over the four seasons, with spatial autocorrelation during winter the most significant.

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