Temporary wetland evolution in the upper Chinchiná river basin and its relationship with ecosystem dynamics

A study was performed regarding high Andean wetland degradation in a paramo area between the municipalities of Villamaría and Manizales, Colombia, by way of multi-temporal analysis, using satellite images from optical sensors, such as LANDSAT and RAPIDEYE, as well as images from RADAR sensors (ALOS PALSAR, SENTINEL 1), and analysis of anthropic and natural factors. As a result, the wetlands have begun a significant, linear decline with 67.9% water mirror loss in a nine-year period. There is also a direct relationship between wetland loss, and decreases in precipitation, and anthropization processes. It was determined, from the anthropic factor analysis, that that livestock and agricultural land use are those which cause the greatest negative effect on wetland decline in the studied area.

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Multi-temporal analysis of vegetation reflectance using MERIS data in the Czech Republic

Miscellanea Geographica ◽

10.2478/mgrsd-2014-0015 ◽

2014 ◽

Vol 18 (2) ◽

pp. 30-34

Author(s):

Přemysl Štych ◽

Lucie Malíková ◽

Jan Kříž ◽

Lukáš Holman

Keyword(s):

Czech Republic ◽

Agricultural Land ◽

Spectral Characteristics ◽

Vegetation Indices ◽

Temporal Analysis ◽

High Temporal Resolution ◽

The Czech Republic ◽

Multi Temporal ◽

Dynamic Landscape ◽

Resolution Data

Abstract Accurate high temporal resolution data is a very important source of information for understanding processes in the landscape. High temporal and spectral resolution data enable the monitoring of dynamic landscape processes. For this reason, since 2008 a receiving station for Metosat, NOAA and Envisat data has been installed at the Department of Applied Geoinformatics and Cartography, Faculty of Science, Charles University in Prague. The aim of this study is to analyse the spectral characteristics of vegetation using MERIS data in the Czech Republic. Spectral characteristics of vegetation were examined both by analysing changes in reflectivity as well as by utilising vegetation indices. Vegetation in forests and agricultural land was evaluated. The results present the spectral characteristics of selected associations of vegetation based on MERIS data and a discussion of the methods of multitemporal classification of land cover.

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Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics

Remote Sensing ◽

10.3390/rs12223831 ◽

2020 ◽

Vol 12 (22) ◽

pp. 3831

Author(s):

Marvin Ludwig ◽

Christian M. Runge ◽

Nicolas Friess ◽

Tiziana L. Koch ◽

Sebastian Richter ◽

...

Keyword(s):

Optical Sensors ◽

Spatial Data ◽

Forest Canopy ◽

Cost Effective ◽

Temporal Analysis ◽

Unmanned Aerial Systems ◽

Wide Range ◽

Very High Spatial Resolution ◽

Multi Temporal ◽

Aerial Systems

Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing.

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Multi-temporal Analysis for Differential Interferometry Synthetic Aperture Radar (D-InSAR) and Its Application to Monitoring Land Surface Displcements

International Journal of Environment and Geosciences ◽

10.24843/ijeg.2017.v01.i01.p01 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Putu Edi Yastika ◽

Norikazu Shimizu ◽

Tasuku Tanaka ◽

Takahiro Osawa

Keyword(s):

Land Surface ◽

Average Rate ◽

Temporal Analysis ◽

Alos Palsar ◽

Subsidence Rate ◽

Time Period ◽

Multi Temporal ◽

Center Area ◽

Component Phase ◽

Displacement Phase

Land subsidence rate in Semarang has been observed by D-InSAR technique based on ALOS-PALSAR data on ascending orbits, which is processed by GMTSAR and ArcGIS software. Two kind of methods namely single D-InSAR and Multi-Temporal D-InSAR has been done. By employing SRTM3 and ASTER1 DEM data to remove the topography component, total 67 pairs of inteferogram has generated. Northeast area and shoreline area has largest subsidence about 20-32 cm for 4 years or average rate 5-8 cm/year. Since the northwest area and center area has lower subsidence rate and even no remarkable subsidence occurred, this area seems to be stable comparing the northeast area. Removing the topography component phase to get displacement phase from the phase interferogram by using SRTM3 DEM and ASTER1 DEM data respectively, the both results coincided with 0.995 correlation value. The coherence threshold is an important factor to get better accuracy, but if setting the threshold too high, the process of interference will be failed and not be able to obtain the results in a lot of area. The perpendicular baseline and the temporal baseline (time period) is an important factor to determining the coherence threshold. By using many scenes the Multi-Temporal D-InSAR was applied, and by selecting good pairs of the interferograms, accuracy of the results will be improved. The correlation value for GPS data eventually increased from 0.63 to 0.77.

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Forest and Industrial Plantation Mapping with Multi-Temporal Dual Polarization by ALOS PALSAR Data In Riau Province

International Journal of Environment and Geosciences ◽

10.24843/ijeg.2018.v02.i01.p04 ◽

2018 ◽

Vol 2 (1) ◽

pp. 35

Author(s):

Elis Molidena ◽

Takahiro Osawa ◽

Putu Gede Ardhana ◽

Abd. Rahman As-syakur

Keyword(s):

Land Use ◽

Ground Truth ◽

Temporal Analysis ◽

Alos Palsar ◽

Ground Truth Data ◽

Multi Temporal ◽

Industrial Plantation ◽

Changes Detection ◽

Accuracy Result ◽

Color Composite

Backscattering characteristics of land use has been analyzed using ALOS PALSAR data. The purpose of this research are mapping of land use by five categories such as forest, acacia, oil palm, open area and water, and to identify the changes of environmental. Analysis Pixel-by-pixel average of ALOS PALSAR level 1.5 backscattering used from five of category land use was to estimate the spectral characteristic of each object in difference HH and HV polarization. Ground truth data was taken from 169 locations which used for classification, 119 locations and 50 locations used for validation. Two different times of ALOS PALSAR level 1.0 2009 and 2010 data, was used for changes detection by multi temporal color composite combination. The accuracy result for classification map shows 62% of ground truth database, and multi temporal analysis showed the possibility of changes.

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Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases

Remote Sensing ◽

10.3390/rs12060943 ◽

2020 ◽

Vol 12 (6) ◽

pp. 943

Author(s):

Andreas Schmitt ◽

Anna Wendleder ◽

Rüdiger Kleynmans ◽

Maximilian Hell ◽

Achim Roth ◽

...

Keyword(s):

Image Fusion ◽

Optical Sensors ◽

Remote Sensing Data ◽

Image Data ◽

Machine Learning Algorithms ◽

Alos Palsar ◽

Data Set ◽

Multi Temporal ◽

The Stability ◽

Sentinel 2

This article spanned a new, consistent framework for production, archiving, and provision of analysis ready data (ARD) from multi-source and multi-temporal satellite acquisitions and an subsequent image fusion. The core of the image fusion was an orthogonal transform of the reflectance channels from optical sensors on hypercomplex bases delivered in Kennaugh-like elements, which are well-known from polarimetric radar. In this way, SAR and Optics could be fused to one image data set sharing the characteristics of both: the sharpness of Optics and the texture of SAR. The special properties of Kennaugh elements regarding their scaling—linear, logarithmic, normalized—applied likewise to the new elements and guaranteed their robustness towards noise, radiometric sub-sampling, and therewith data compression. This study combined Sentinel-1 and Sentinel-2 on an Octonion basis as well as Sentinel-2 and ALOS-PALSAR-2 on a Sedenion basis. The validation using signatures of typical land cover classes showed that the efficient archiving in 4 bit images still guaranteed an accuracy over 90% in the class assignment. Due to the stability of the resulting class signatures, the fuzziness to be caught by Machine Learning Algorithms was minimized at the same time. Thus, this methodology was predestined to act as new standard for ARD remote sensing data with an subsequent image fusion processed in so-called data cubes.

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Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

Remote Sensing ◽

10.3390/rs12193226 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3226

Author(s):

Daniel Cunningham ◽

Paul Cunningham ◽

Matthew E. Fagan

Keyword(s):

Costa Rica ◽

Forest Cover ◽

Agricultural Land ◽

Forest Area ◽

Tree Cover ◽

Agricultural Crop ◽

Forest Change ◽

Alos Palsar ◽

Tropical Regions ◽

The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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Analysis of spatiotemporal changes of agricultural land after the Second World War in Czechia

Scientific Reports ◽

10.1038/s41598-021-91946-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Vít Zelinka ◽

Johana Zacharová ◽

Jan Skaloš

Keyword(s):

Land Use ◽

Agricultural Land ◽

Population Change ◽

Temporal Analysis ◽

Second World War ◽

Agricultural Landscapes ◽

German Population ◽

World War ◽

Landscape Type ◽

Second World

AbstractThe term Sudetenland refers to large regions of the former Czechoslovakia that had been dominated by Germans. German population was expelled directly after the Second World War, between 1945 and 1947. Almost three million people left large areas in less than two years. This population change led to a break in the relationship between the people and the landscape. The aim of the study is to compare the trajectories of these changes in agricultural landscapes in lower and higher altitudes, both in depopulated areas and areas with preserved populations. This study included ten sites in the region of Northern Bohemia in Czechia (18,000 ha in total). Five of these sites represent depopulated areas, and the other five areas where populations remained preserved. Changes in the landscape were assessed through a bi-temporal analysis of land use change by using aerial photograph data from time hoirzons of 2018 and 1953. Land use changes from the 1950s to the present are corroborated in the studied depopulated and preserved areas mainly by the trajectory of agricultural land to forest. The results prove that both population displacement and landscape type are important factors that affect landscape changes, especially in agricultural landscapes.

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Multi-temporal analysis for drought classifying based on SPEI gridded data and hybrid maximal overlap discrete wavelet transform

International Journal of Environmental Science and Technology ◽

10.1007/s13762-021-03453-5 ◽

2021 ◽

Author(s):

K. Roushangar ◽

R. Ghasempour

Keyword(s):

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Temporal Analysis ◽

Discrete Wavelet ◽

Gridded Data ◽

Multi Temporal

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A Proposed Land Exchange Algorithm for Eliminating the External Plot Patchwork

Land ◽

10.3390/land10010064 ◽

2021 ◽

Vol 10 (1) ◽

pp. 64

Author(s):

Żanna Stręk ◽

Przemysław Leń ◽

Justyna Wójcik-Leń ◽

Paweł Postek ◽

Monika Mika ◽

...

Keyword(s):

Spatial Structure ◽

Rural Areas ◽

Agricultural Land ◽

Test Sample ◽

Practical Application ◽

Exchange Algorithm ◽

The World ◽

Negative Effect ◽

Structure Improvement ◽

Land Exchange

In many countries of the world, rural areas are characterized by a defective spatial structure of agricultural land. The most frequent defects are large fragmentation and distribution of farmland. The fragmentation of land has been an issue widely described by many authors throughout the world. The problem of the distribution of land owned by individual farmers is slightly different, since due to the complexity of the problem this issue was not widely explored in Poland (plot patchwork) or in other countries of Europe and the world. Land fragmentation and distribution of plots in rural areas has a negative effect on the profitability and efficiency of agricultural production. Land consolidation and exchange is an operation facilitating spatial structure improvement. The authors attempted to develop a universal land exchange algorithm for eliminating the external plot patchwork. As it turns out, so far no land exchange algorithm has been developed. Specific analyses were carried out in Puchaczów commune, county of Łęczna, Lublin voivodeship in the eastern part of Poland, covering an area of 6907.80 ha, split into 15,211 plots. The chequerboard arrays method was used. The publication presents the algorithm and its practical application using a test sample. A result of the studies is a proposal concerning the exchange of land between landowners in the villages of the commune of Puchaczów. Using the algorithm, the area of individual lands in the commune, after the exchange, will increase by 172.09 ha, which is 2.5% for the area of individual lands, and 1.9% for the commune.

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