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Navigation: Home \ Graphic Apps \ CAD \ RTOPO LT We're sorry. This software is no longer available for viewing. Related RTOPO LT Vista Software Terra Excess 25.1217 download by Terra Excess Software Terra Excess is land surveying and civil engineering CAD software developed to be extremely intuitive. Even by ... just a few minutes - GENERATING AND LABELING CONTOUR LINES IN ORDER TO PRODUCE TOPOGRAPHIC PLANS AND ... type: Shareware ($298.00) categories: land surveying, civil engineering, topographic, contour lines, contour map, triangulated irregular network, earthworks, volumetric, volume calculation, cut and fill, volumes, estimating volumes, survey points, CAD, DXF, quarries, tin surface View Details Download TrueSpace 7.61 download by Caligari Corporation ... and movies, you can also make 3D content for online shared spaces, and for Virtual Earth. Features: Export to Virtual ... game engines such as XNA to develop games for Windows or the Xbox 360. · Also ... View Details Download Navigation: Home \ Graphic Apps \ CAD \ TopoLT Software Info Best Vista Download periodically updates pricing and software information of TopoLT full version from the publisher, but some information may be out-of-date. You should confirm all information. Software piracy is theft, using crack, warez passwords, patches, serial numbers, registration codes, key generator, keymaker or keygen for TopoLT license key is illegal and prevent future development of TopoLT. Download links are directly from our mirrors or publisher's website, TopoLT torrent files or shared files from rapidshare, yousendit or megaupload are not allowed! Released: October 16, 2023 Filesize: 67.80 MB Platform: Windows XP, Windows Vista, Windows Vista x64, Windows 7, Windows 7 x64, Windows 8, Windows 8 x64, Windows 10, Windows 10 x64, Windows 11 Install Instal And Uninstall Add Your Review or Windows Vista Compatibility Report TopoLT - Releases History Software: TopoLT 15.2 Date Released: Oct 16, 2023 Status: New Release Software: TopoLT 15.1 Date Released: Mar 3, 2023 Status: New Release Software: TopoLT 14.0 Date Released: Feb 24, 2022 Status: New Release Most popular cut and fill volume in CAD downloads for Vista Terra Excess 25.1217 download by Terra Excess Software Terra Excess is land surveying and civil engineering CAD software developed to be extremely ... tasks in just a few minutes - GENERATING AND LABELING CONTOUR LINES IN ORDER TO PRODUCE TOPOGRAPHIC ... type: Shareware ($298.00) categories: land surveying, civil engineering, topographic, contour lines, contour map, triangulated irregular network, earthworks, volumetric, volume calculation, cut and fill, volumes, estimating volumes, survey points, CAD, DXF, quarries, tin surface View Details DownloadPartners of TERRA - TERRA Group - terra-world.com
Not meet our criteria. A common use case is filtering items based on their cloud coverage. For instance, if we want to download Sentinel-2 imagery with cloud cover below 25%, we can define our query function as follows:sentinel2_25cc_qf We could pass it in using the code get_stac_data(query_function = sentinel2_25cc_qf). This is an optional argument, as rsi provides a default query function. We can then continue our work with the results stored in swarzedz_sentinel2_sep, selecting two images that have low cloud coverage.swarzedz_sentinel2_07_09 = terra::rast(swarzedz_sentinel2_sep[16])swarzedz_sentinel2_09_27 = terra::rast(swarzedz_sentinel2_sep[1])rsi’s calculate_indices() requires a data frame of indices to calculate. Since we want to calculate NDVI, all we need to do is extract the row with NDVI’s formula. We can use the short_name column for that.ndvi = asi[asi$short_name == "NDVI", ]swarzedz_sentinel2_07_09_ndvi = calculate_indices( swarzedz_sentinel2_07_09, ndvi, output_filename = tempfile(fileext = ".tif"))swarzedz_sentinel2_09_27_ndvi = calculate_indices( swarzedz_sentinel2_09_27, ndvi, output_filename = tempfile(fileext = ".tif"))swarzedz_sentinel2_07_09_ndvi[1] "/tmp/Rtmppind2Y/file501084d439b94.tif"We now can plot both rasters to see the values that were calculated for both dates.par(mfrow = c(1, 2))swarzedz_sentinel2_07_09_ndvi_rast = terra::rast(swarzedz_sentinel2_07_09_ndvi)swarzedz_sentinel2_09_27_ndvi_rast = terra::rast(swarzedz_sentinel2_09_27_ndvi)terra::plot(swarzedz_sentinel2_07_09_ndvi_rast, range = c(-1, 1))terra::plot(swarzedz_sentinel2_09_27_ndvi_rast, range = c(-1, 1))To better visualize the change in NDVI over time, we can create a difference raster. Values above 0 indicate that NDVI was higher on October 27 than on July 9. Values below 0 indicate that the NDVI values decreased on October 27, compared to July 9. Values equal to 0 mean that NDVI values haven’t changed over time.par(mfrow = c(1, 2))dif = swarzedz_sentinel2_09_27_ndvi_rast - swarzedz_sentinel2_07_09_ndvi_rastterra::plot(dif)hist(dif, main = "", xlab = "NDVI")We can save both rasters as one, using stack_rasters() function.stack = stack_rasters( c( swarzedz_sentinel2_07_09_ndvi, swarzedz_sentinel2_09_27_ndvi ), tempfile(fileext = ".vrt"))stack_rast = terra::rast(stack)names(stack_rast) = c("NDVI 07.09", "NDVI 09.27")stack_rastclass : SpatRaster dimensions : 1000, 1000, 2 (nrow, ncol, nlyr)resolution : 10, 10 (x, y)extent : 366347.1, 376347.1, 501106.3, 511106.3 (xmin, xmax, ymin, ymax)coord. ref. : ETRF2000-PL / CS92 (EPSG:2180) source : file5010876ee0652.vrt names : NDVI 07.09, NDVI 09.27 min values : -0.1237687, -0.5265973 max values : 0.7251614, 0.7040647 terra::plot(stack_rast, range = c(-1, 1))ConclusionThe goal of this article was to demonstrate the capabilities of rsi package on the most common examples in remote sensing tasks. It’s current state already shows huge potential in many remote sensing applications. rsi provides functions which simplify processes of downloading satellite imagery and calculating spectral indices. If you want to learn more about rsi package, you can visit GitHub repository of the project.While working on this article, I found many posibble features that could be added into rsi. An useful feature would be adding methods of simpler product filtering, based on cloud coverage and other parameters. Other feature could be focused on time series analysis, by calculating indices for each available item in selected time span.I’m looking forward into the future developements of rsi.ReuseCitationBibTeX citation:@online{rydzik2024, author. Download Terra Wars [NL] Скачать Terra Wars [RU] Ladda ner Terra Wars [SV] T l charger Terra Wars [FR] Download do Terra Wars [PT] Unduh Terra Wars [ID] Descargar Terra Wars [ES] Terra Wars indir [TR] 下载Terra Wars [ZH] Terra Wars for iPhone. Free. In English; V 1.0; 4.6 (0) Security Status.TERRA Rent - TERRA Group - terra-world.com
We stand at the threshold of a new era of precision medicine, where health and life sciences data hold the potential to dramatically propel and expand our understanding and treatment of human disease. One of the tools that we believe will help to enable precision medicine is Terra, the secure biomedical research platform co-developed by Broad Institute of MIT and Harvard, Microsoft, and Verily. Today, we are excited to share that Terra is available for preview on Microsoft Azure.Starting today, any researcher can bring their data, access publicly available datasets, run analyses, and collaborate with others on Terra using Microsoft Azure. Learn more about accessing Terra and exploring its capabilities on the Terra blog (opens in new tab).By joining forces on Terra, the Broad Institute, Microsoft, and Verily are accelerating the next generation of collaborative biomedical research to positively impact health outcomes now and in the future. Terra’s cloud-based platform offers a secure, centralized location for biomedical research, connecting researchers to each other and to the datasets and tools they need to collaborate effectively, advance their work, and achieve scientific breakthroughs. Terra on Azure will also provide valuable support for enterprise organizations across industries. Terra on Azure is built to be enterprise-ready and natively supports single sign-on (SSO) with Azure Active Directory. Operating as platform as a service (PaaS), Terra deploys resources into an end-user’s Azure tenant, allowing customers to apply their Enterprise Agreements to their use of Terra and giving them more control over the cloud resources running in A point in San Antonio.library(sf)san_antonio = st_point(c(-98.491142, 29.424349))san_antonio = st_sfc(san_antonio, crs = "EPSG:4326")san_antonio = st_buffer(st_transform(san_antonio, "EPSG:3081"), 5000)Having specified the area of interest, we can create our query. We will start with downloading Landsat data for September and October 2023 and save it to a temporary file.sa_landsat = get_landsat_imagery( san_antonio, start_date = "2023-09-01", end_date = "2023-10-31", output_filename = tempfile(fileext = ".tif"))sa_landsat[1] "/tmp/Rtmppind2Y/file501082fbc26c0.tif"get_stac_data() and its child functions return the path to downloaded image. As a default, they create the composite image out of median values of all avaiable images for specified time span. We can specify other composite functions, like mean, sum, min or max. We can also not use composite function at all (composite_function = NULL), and obtain all available images for specified time span. Another default argument, passed in for mask_band, automatically masks clouds with NAs.sa_sentinel2 = get_sentinel2_imagery( san_antonio, start_date = "2023-09-01", end_date = "2023-10-31", output_filename = tempfile(fileext = ".tif"))In this example, we download Sentinel 2 images for September and October 2023, mask out clouds, and create a composite image.Let’s also obtain the DEM of our area.sa_dem = get_dem( san_antonio, output_filename = tempfile(fileext = ".tif"))After downloading the images, we can load them into SpatRaster objects using rast(). rsi automatically assigns proper band names to it, which follow Awesome Spectral Indices standard.library(terra)sa_landsat_rast = terra::rast(sa_landsat)sa_sentinel2_rast = terra::rast(sa_sentinel2)sa_dem_rast = terra::rast(sa_dem)sa_landsat_rastclass : SpatRaster dimensions : 333, 333, 8 (nrow, ncol, nlyr)resolution : 30, 30 (x, y)extent : 1141170, 1151160, 803238.9, 813228.9 (xmin, xmax, ymin, ymax)coord. ref. : NAD83 / Texas State Mapping System (EPSG:3081) source : file501082fbc26c0.tif names : A, B, G, R, N, S1, ... We can plot the rasters together to compare Landsat and Sentinel images and visualize DEM.par(mfrow = c(1, 3))terra::plotRGB(sa_landsat_rast, r = 4, g = 3, b = 2, stretch = "lin")terra::plotRGB(sa_sentinel2_rast, r = 4, g = 3, b = 2, stretch = "lin")terra::plot(sa_dem_rast)Having downloaded images, we can use them to calculate spectral indices. In this example, we will observe the change in vegetation between two dates for the Swarzędz area in Poland. Let’s start by creating a new area of interest.swarzedz = st_point(c(17.108174, 52.405725))swarzedz = st_set_crs(st_sfc(swarzedz), "EPSG:4326")swarzedz = st_buffer(st_transform(swarzedz, "EPSG:2180"), 5000)For the most accurate results, we will use Sentinel 2 data. The date span is set from July to September 2023. We will also pass in composite_function = NULL, so that all available images will be downloaded separately.swarzedz_sentinel2_sep = get_sentinel2_imagery( swarzedz, start_date = "2023-07-01", end_date = "2023-09-30", output_filename = tempfile(fileext = ".tif"), composite_function = NULL)swarzedz_sentinel2_sep [1] "/tmp/Rtmppind2Y/file5010818963908_2023-09-27T10:00:31.024000Z.tif" [2] "/tmp/Rtmppind2Y/file5010818963908_2023-09-22T09:56:49.024000Z.tif" [3] "/tmp/Rtmppind2Y/file5010818963908_2023-09-17T10:00:31.024000Z.tif" [4] "/tmp/Rtmppind2Y/file5010818963908_2023-09-12T09:56:09.024000Z.tif" [5] "/tmp/Rtmppind2Y/file5010818963908_2023-09-07T10:00:31.024000Z.tif" [6] "/tmp/Rtmppind2Y/file5010818963908_2023-09-02T09:55:59.024000Z.tif" [7] "/tmp/Rtmppind2Y/file5010818963908_2023-08-28T10:00:31.025000Z.tif" [8] "/tmp/Rtmppind2Y/file5010818963908_2023-08-23T09:55:59.024000Z.tif" [9] "/tmp/Rtmppind2Y/file5010818963908_2023-08-18T10:00:31.024000Z.tif"[10] "/tmp/Rtmppind2Y/file5010818963908_2023-08-13T09:55:59.024000Z.tif"[11] "/tmp/Rtmppind2Y/file5010818963908_2023-08-08T10:00:31.024000Z.tif"[12] "/tmp/Rtmppind2Y/file5010818963908_2023-08-03T09:55:59.024000Z.tif"[13] "/tmp/Rtmppind2Y/file5010818963908_2023-07-29T10:00:31.024000Z.tif"[14] "/tmp/Rtmppind2Y/file5010818963908_2023-07-19T10:00:31.024000Z.tif"[15] "/tmp/Rtmppind2Y/file5010818963908_2023-07-14T09:55:59.024000Z.tif"[16] "/tmp/Rtmppind2Y/file5010818963908_2023-07-09T10:00:31.024000Z.tif"[17] "/tmp/Rtmppind2Y/file5010818963908_2023-07-04T09:55:59.024000Z.tif"rsi allows for creating custom query functions using CQL2, which we can use to filter out products that doTERRA Partners - TERRA Group - terra-world.com
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IBreviary TS Pro Terra Sancta is the application that brings the traditional Catholic prayer of the Breviary and all the texts of the Liturgy on your iPhone, iPad and iPod.This app wants to contribute, through a partnership with Custody of the Holy Land, friendship and prayer for all Christians living Holy Places.iBreviary contains:• Breviary, Missal and Lectionary complete in 10 languages and continuously updated (Italian, English, Spanish, French, Romanian, Arabic, Portuguese, Turkish, Latin and Galician)• The text of the Breviary and the Missal in the "Latin Vetus Ordo" and Latin• All the main prayers of the Christian• Rituals for the sacraments and celebrations• The liturgical texts used in the Holy LandAlso iBreviary "Pro Terra Sancta" offers:• The section, "Rites", with all the rituals and texts for the various celebrations Catholic (Adoration of the Eucharist, the Sacraments, Blessings, etc.)• The brand new "Terra Sancta" the liturgical texts used in the Holy Land• Keep in touch through the blog and the pages of the Franciscans Holy Places• A rich section dedicated to Saints• Store a day on any device• Full management of saved days (selection and cancellation)• Store up to 14 days (something very much in demand by those who want to download a bit of days for travel or long period without internet access)• Download the entire week• Enlarge and diminish the text dimension, with the flick of the fingers on the screen• The ability to adjust the color of the background, the font and the size for a better reading of texts• (On iPad only) Create and manage your MissalThe Application is available in the following languages:• English• Italian• Spanish• French• Romanian• Arabic• Portuguese• Turkishand contains the liturgical texts in the following languages:• Italian• English• Spanish• French• Romanian• Latin• Arabian• Turkish• Galician• Vetus Ordo• Rito Ambrosiano• Rito Monastico.The Languages of the liturgical texts are constantly updated.Owner, creator and founder: Paolo PadriniDeveloper: Art & Coop Società Cooperativa. Download Terra Wars [NL] Скачать Terra Wars [RU] Ladda ner Terra Wars [SV] T l charger Terra Wars [FR] Download do Terra Wars [PT] Unduh Terra Wars [ID] Descargar Terra Wars [ES] Terra Wars indir [TR] 下载Terra Wars [ZH] Terra Wars for iPhone. Free. In English; V 1.0; 4.6 (0) Security Status. Terra Smash for Android, free and safe download. Terra Smash latest version: Terra Smash: Shape Worlds with Destruction and Creation. Terra Smash is aAbout TERRA Group - TERRA Group - terra-world.com
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Navigation: Home \ Graphic Apps \ CAD \ RTOPO LT We're sorry. This software is no longer available for viewing. Related RTOPO LT Vista Software Terra Excess 25.1217 download by Terra Excess Software Terra Excess is land surveying and civil engineering CAD software developed to be extremely intuitive. Even by ... just a few minutes - GENERATING AND LABELING CONTOUR LINES IN ORDER TO PRODUCE TOPOGRAPHIC PLANS AND ... type: Shareware ($298.00) categories: land surveying, civil engineering, topographic, contour lines, contour map, triangulated irregular network, earthworks, volumetric, volume calculation, cut and fill, volumes, estimating volumes, survey points, CAD, DXF, quarries, tin surface View Details Download TrueSpace 7.61 download by Caligari Corporation ... and movies, you can also make 3D content for online shared spaces, and for Virtual Earth. Features: Export to Virtual ... game engines such as XNA to develop games for Windows or the Xbox 360. · Also ... View Details Download
2025-04-23Navigation: Home \ Graphic Apps \ CAD \ TopoLT Software Info Best Vista Download periodically updates pricing and software information of TopoLT full version from the publisher, but some information may be out-of-date. You should confirm all information. Software piracy is theft, using crack, warez passwords, patches, serial numbers, registration codes, key generator, keymaker or keygen for TopoLT license key is illegal and prevent future development of TopoLT. Download links are directly from our mirrors or publisher's website, TopoLT torrent files or shared files from rapidshare, yousendit or megaupload are not allowed! Released: October 16, 2023 Filesize: 67.80 MB Platform: Windows XP, Windows Vista, Windows Vista x64, Windows 7, Windows 7 x64, Windows 8, Windows 8 x64, Windows 10, Windows 10 x64, Windows 11 Install Instal And Uninstall Add Your Review or Windows Vista Compatibility Report TopoLT - Releases History Software: TopoLT 15.2 Date Released: Oct 16, 2023 Status: New Release Software: TopoLT 15.1 Date Released: Mar 3, 2023 Status: New Release Software: TopoLT 14.0 Date Released: Feb 24, 2022 Status: New Release Most popular cut and fill volume in CAD downloads for Vista Terra Excess 25.1217 download by Terra Excess Software Terra Excess is land surveying and civil engineering CAD software developed to be extremely ... tasks in just a few minutes - GENERATING AND LABELING CONTOUR LINES IN ORDER TO PRODUCE TOPOGRAPHIC ... type: Shareware ($298.00) categories: land surveying, civil engineering, topographic, contour lines, contour map, triangulated irregular network, earthworks, volumetric, volume calculation, cut and fill, volumes, estimating volumes, survey points, CAD, DXF, quarries, tin surface View Details Download
2025-04-15Not meet our criteria. A common use case is filtering items based on their cloud coverage. For instance, if we want to download Sentinel-2 imagery with cloud cover below 25%, we can define our query function as follows:sentinel2_25cc_qf We could pass it in using the code get_stac_data(query_function = sentinel2_25cc_qf). This is an optional argument, as rsi provides a default query function. We can then continue our work with the results stored in swarzedz_sentinel2_sep, selecting two images that have low cloud coverage.swarzedz_sentinel2_07_09 = terra::rast(swarzedz_sentinel2_sep[16])swarzedz_sentinel2_09_27 = terra::rast(swarzedz_sentinel2_sep[1])rsi’s calculate_indices() requires a data frame of indices to calculate. Since we want to calculate NDVI, all we need to do is extract the row with NDVI’s formula. We can use the short_name column for that.ndvi = asi[asi$short_name == "NDVI", ]swarzedz_sentinel2_07_09_ndvi = calculate_indices( swarzedz_sentinel2_07_09, ndvi, output_filename = tempfile(fileext = ".tif"))swarzedz_sentinel2_09_27_ndvi = calculate_indices( swarzedz_sentinel2_09_27, ndvi, output_filename = tempfile(fileext = ".tif"))swarzedz_sentinel2_07_09_ndvi[1] "/tmp/Rtmppind2Y/file501084d439b94.tif"We now can plot both rasters to see the values that were calculated for both dates.par(mfrow = c(1, 2))swarzedz_sentinel2_07_09_ndvi_rast = terra::rast(swarzedz_sentinel2_07_09_ndvi)swarzedz_sentinel2_09_27_ndvi_rast = terra::rast(swarzedz_sentinel2_09_27_ndvi)terra::plot(swarzedz_sentinel2_07_09_ndvi_rast, range = c(-1, 1))terra::plot(swarzedz_sentinel2_09_27_ndvi_rast, range = c(-1, 1))To better visualize the change in NDVI over time, we can create a difference raster. Values above 0 indicate that NDVI was higher on October 27 than on July 9. Values below 0 indicate that the NDVI values decreased on October 27, compared to July 9. Values equal to 0 mean that NDVI values haven’t changed over time.par(mfrow = c(1, 2))dif = swarzedz_sentinel2_09_27_ndvi_rast - swarzedz_sentinel2_07_09_ndvi_rastterra::plot(dif)hist(dif, main = "", xlab = "NDVI")We can save both rasters as one, using stack_rasters() function.stack = stack_rasters( c( swarzedz_sentinel2_07_09_ndvi, swarzedz_sentinel2_09_27_ndvi ), tempfile(fileext = ".vrt"))stack_rast = terra::rast(stack)names(stack_rast) = c("NDVI 07.09", "NDVI 09.27")stack_rastclass : SpatRaster dimensions : 1000, 1000, 2 (nrow, ncol, nlyr)resolution : 10, 10 (x, y)extent : 366347.1, 376347.1, 501106.3, 511106.3 (xmin, xmax, ymin, ymax)coord. ref. : ETRF2000-PL / CS92 (EPSG:2180) source : file5010876ee0652.vrt names : NDVI 07.09, NDVI 09.27 min values : -0.1237687, -0.5265973 max values : 0.7251614, 0.7040647 terra::plot(stack_rast, range = c(-1, 1))ConclusionThe goal of this article was to demonstrate the capabilities of rsi package on the most common examples in remote sensing tasks. It’s current state already shows huge potential in many remote sensing applications. rsi provides functions which simplify processes of downloading satellite imagery and calculating spectral indices. If you want to learn more about rsi package, you can visit GitHub repository of the project.While working on this article, I found many posibble features that could be added into rsi. An useful feature would be adding methods of simpler product filtering, based on cloud coverage and other parameters. Other feature could be focused on time series analysis, by calculating indices for each available item in selected time span.I’m looking forward into the future developements of rsi.ReuseCitationBibTeX citation:@online{rydzik2024, author
2025-04-22We stand at the threshold of a new era of precision medicine, where health and life sciences data hold the potential to dramatically propel and expand our understanding and treatment of human disease. One of the tools that we believe will help to enable precision medicine is Terra, the secure biomedical research platform co-developed by Broad Institute of MIT and Harvard, Microsoft, and Verily. Today, we are excited to share that Terra is available for preview on Microsoft Azure.Starting today, any researcher can bring their data, access publicly available datasets, run analyses, and collaborate with others on Terra using Microsoft Azure. Learn more about accessing Terra and exploring its capabilities on the Terra blog (opens in new tab).By joining forces on Terra, the Broad Institute, Microsoft, and Verily are accelerating the next generation of collaborative biomedical research to positively impact health outcomes now and in the future. Terra’s cloud-based platform offers a secure, centralized location for biomedical research, connecting researchers to each other and to the datasets and tools they need to collaborate effectively, advance their work, and achieve scientific breakthroughs. Terra on Azure will also provide valuable support for enterprise organizations across industries. Terra on Azure is built to be enterprise-ready and natively supports single sign-on (SSO) with Azure Active Directory. Operating as platform as a service (PaaS), Terra deploys resources into an end-user’s Azure tenant, allowing customers to apply their Enterprise Agreements to their use of Terra and giving them more control over the cloud resources running in
2025-04-23A point in San Antonio.library(sf)san_antonio = st_point(c(-98.491142, 29.424349))san_antonio = st_sfc(san_antonio, crs = "EPSG:4326")san_antonio = st_buffer(st_transform(san_antonio, "EPSG:3081"), 5000)Having specified the area of interest, we can create our query. We will start with downloading Landsat data for September and October 2023 and save it to a temporary file.sa_landsat = get_landsat_imagery( san_antonio, start_date = "2023-09-01", end_date = "2023-10-31", output_filename = tempfile(fileext = ".tif"))sa_landsat[1] "/tmp/Rtmppind2Y/file501082fbc26c0.tif"get_stac_data() and its child functions return the path to downloaded image. As a default, they create the composite image out of median values of all avaiable images for specified time span. We can specify other composite functions, like mean, sum, min or max. We can also not use composite function at all (composite_function = NULL), and obtain all available images for specified time span. Another default argument, passed in for mask_band, automatically masks clouds with NAs.sa_sentinel2 = get_sentinel2_imagery( san_antonio, start_date = "2023-09-01", end_date = "2023-10-31", output_filename = tempfile(fileext = ".tif"))In this example, we download Sentinel 2 images for September and October 2023, mask out clouds, and create a composite image.Let’s also obtain the DEM of our area.sa_dem = get_dem( san_antonio, output_filename = tempfile(fileext = ".tif"))After downloading the images, we can load them into SpatRaster objects using rast(). rsi automatically assigns proper band names to it, which follow Awesome Spectral Indices standard.library(terra)sa_landsat_rast = terra::rast(sa_landsat)sa_sentinel2_rast = terra::rast(sa_sentinel2)sa_dem_rast = terra::rast(sa_dem)sa_landsat_rastclass : SpatRaster dimensions : 333, 333, 8 (nrow, ncol, nlyr)resolution : 30, 30 (x, y)extent : 1141170, 1151160, 803238.9, 813228.9 (xmin, xmax, ymin, ymax)coord. ref. : NAD83 / Texas State Mapping System (EPSG:3081) source : file501082fbc26c0.tif names : A, B, G, R, N, S1, ... We can plot the rasters together to compare Landsat and Sentinel images and visualize DEM.par(mfrow = c(1, 3))terra::plotRGB(sa_landsat_rast, r = 4, g = 3, b = 2, stretch = "lin")terra::plotRGB(sa_sentinel2_rast, r = 4, g = 3, b = 2, stretch = "lin")terra::plot(sa_dem_rast)Having downloaded images, we can use them to calculate spectral indices. In this example, we will observe the change in vegetation between two dates for the Swarzędz area in Poland. Let’s start by creating a new area of interest.swarzedz = st_point(c(17.108174, 52.405725))swarzedz = st_set_crs(st_sfc(swarzedz), "EPSG:4326")swarzedz = st_buffer(st_transform(swarzedz, "EPSG:2180"), 5000)For the most accurate results, we will use Sentinel 2 data. The date span is set from July to September 2023. We will also pass in composite_function = NULL, so that all available images will be downloaded separately.swarzedz_sentinel2_sep = get_sentinel2_imagery( swarzedz, start_date = "2023-07-01", end_date = "2023-09-30", output_filename = tempfile(fileext = ".tif"), composite_function = NULL)swarzedz_sentinel2_sep [1] "/tmp/Rtmppind2Y/file5010818963908_2023-09-27T10:00:31.024000Z.tif" [2] "/tmp/Rtmppind2Y/file5010818963908_2023-09-22T09:56:49.024000Z.tif" [3] "/tmp/Rtmppind2Y/file5010818963908_2023-09-17T10:00:31.024000Z.tif" [4] "/tmp/Rtmppind2Y/file5010818963908_2023-09-12T09:56:09.024000Z.tif" [5] "/tmp/Rtmppind2Y/file5010818963908_2023-09-07T10:00:31.024000Z.tif" [6] "/tmp/Rtmppind2Y/file5010818963908_2023-09-02T09:55:59.024000Z.tif" [7] "/tmp/Rtmppind2Y/file5010818963908_2023-08-28T10:00:31.025000Z.tif" [8] "/tmp/Rtmppind2Y/file5010818963908_2023-08-23T09:55:59.024000Z.tif" [9] "/tmp/Rtmppind2Y/file5010818963908_2023-08-18T10:00:31.024000Z.tif"[10] "/tmp/Rtmppind2Y/file5010818963908_2023-08-13T09:55:59.024000Z.tif"[11] "/tmp/Rtmppind2Y/file5010818963908_2023-08-08T10:00:31.024000Z.tif"[12] "/tmp/Rtmppind2Y/file5010818963908_2023-08-03T09:55:59.024000Z.tif"[13] "/tmp/Rtmppind2Y/file5010818963908_2023-07-29T10:00:31.024000Z.tif"[14] "/tmp/Rtmppind2Y/file5010818963908_2023-07-19T10:00:31.024000Z.tif"[15] "/tmp/Rtmppind2Y/file5010818963908_2023-07-14T09:55:59.024000Z.tif"[16] "/tmp/Rtmppind2Y/file5010818963908_2023-07-09T10:00:31.024000Z.tif"[17] "/tmp/Rtmppind2Y/file5010818963908_2023-07-04T09:55:59.024000Z.tif"rsi allows for creating custom query functions using CQL2, which we can use to filter out products that do
2025-04-19