cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6368001
title: Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis

description: A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.


Contents:



	
..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.
	
..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs.
	

		
drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.
		
drainages_original - Drainges identified in the original DEM stored as GeoTIFF. 
	
	
	
..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs.
	

		
LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. 
		
LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. 
	
	
	
..\visibility\ - Viewsheds computed over the original and filtered DEMs.
	

		
Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice.
		

			
Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. 
			
Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. 
			
observer_points - Observer points used for calculating the viewsheds.
		
		
		
regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds.
		

			
visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.
			
visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. 
			
visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.
			
visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.
		
		
	
	



 


Preprint version of the related paper:


Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: https://ssrn.com/abstract=4063514
DOI: 10.57782/rzm27t/tqsjsq
title: sub-s035_task-clean_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/favzk1
title: sub-s034_task-clean_run-2_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/kl67zb
title: sub-s034_task-noisy_run-1_events.tsv

description: :unav
DOI: 10.57782/rzm27t/nfj2xe
title: sub-s032_magnitude2.nii.gz

description: :unav
DOI: 10.57782/rzm27t/yvzbck
title: sub-s034_magnitude2.nii.gz

description: :unav
DOI: 10.57782/rzm27t/2cdfaf
title: sub-s034_task-audiovisual_run-1_events.tsv

description: :unav
DOI: 10.57782/rzm27t/uwfc6i
title: sub-s034_phasediff.json

description: :unav
DOI: 10.57782/rzm27t/sftgpz
title: sub-s034_task-clean_run-2_bold.json

description: :unav
DOI: 10.57782/rzm27t/8blkhs
title: sub-s033_task-noisy_run-2_bold.json

description: :unav
DOI: 10.57782/rzm27t/ex2dte
title: sub-s034_task-noisy_run-1_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/4t5hv0
title: sub-s031_magnitude2.nii.gz

description: :unav
DOI: 10.57782/rzm27t/9wt60y
title: sub-s034_task-audiovisual_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/dgqvsk
title: sub-s032_task-audiovisual_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/k4w4rk
title: sub-s033_T1w.nii.gz

description: :unav
DOI: 10.57782/rzm27t/me1ahj
title: sub-s032_task-rest_bold.json

description: :unav
DOI: 10.57782/rzm27t/ay5ruk
title: sub-s033_task-noisy_run-2_events.tsv

description: :unav
DOI: 10.57782/rzm27t/tdqx8h
title: sub-s034_task-clean_run-2_events.tsv

description: :unav
DOI: 10.57782/rzm27t/4oic46
title: sub-s035_task-rest_sbref.json

description: :unav
DOI: 10.57782/rzm27t/4t0ses
title: sub-s033_task-noisy_run-2_events.json

description: :unav
DOI: 10.57782/rzm27t/icqyie
title: sub-s031_task-noisy_run-2_sbref.json

description: :unav
DOI: 10.57782/rzm27t/b13rda
title: sub-s034_task-rest_bold.json

description: :unav
DOI: 10.57782/rzm27t/uvjdke
title: sub-s031_task-audiovisual_run-1_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/bmx9xz
title: sub-s032_task-audiovisual_run-2_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/swjb9k
title: sub-s034_task-noisy_run-1_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/qrlvzw
title: sub-s035_task-clean_run-2_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/xpghov
title: sub-s032_task-noisy_run-1_sbref.json

description: :unav
DOI: 10.25326/420
title: Wet deposition flux of insoluble atmospheric particles, M’Bour, Senegal

description: Wet deposition flux of insoluble atmospheric particles was collected using a passive MTX ARS 1010 automatic deposition sampler (MTX Italia SPA, Modane, Italy). The collector was made of two buckets (30 cm diameter) and a humidity sensor activated an aluminium lid to cover or uncover the buckets whether in case of rain or not. Following the WMO GAW recommendations, the collector opened within 5 seconds of the onset of precipitation of any type or rate; it closed within 120 seconds of the cessation of precipitation. The collector did not open in the absence of precipitation. It was installed on the roof of a building (i.e. at about 10 m above the ground level) of the geophysical station of the Institut de Recherche pour le Développement (IRD) installed in a nature reserve of 50 ha, and 80 m from the seaside. The samples were collected manually with a weekly time-step or after each precipitation event. The collection procedure was decomposed into three main phases: (1) rinsing with a large volume of water, (2) decantation during more than 6 hours and siphoning of excess water; (3) drying in an oven at 70°C until complete water evaporation. The collected dust was finally weighted in a pre-weighted pillbox with a balance having a precision of 0.0001 g. Wet deposition flux of insoluble atmospheric particles is expressed as g/m² per sampling period and as g/m²/day by dividing the collected mass by surface of collection and sampling duration (dates of start and end of sampling are given in the data files in UTC). Fluxes are given after subtracting blanks; the blank value is given in the header of each file.
DOI: 10.57782/rzm27t/wm3gdp
title: sub-s033_task-audiovisual_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/idbpef
title: sub-s032_magnitude1.nii.gz

description: :unav
DOI: 10.57782/rzm27t/jyyg7h
title: sub-s035_task-audiovisual_run-1_events.json

description: :unav
DOI: 10.57782/rzm27t/z0fjlt
title: sub-s031_task-clean_run-1_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/ojndou
title: sub-s031_task-noisy_run-2_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/6ubspc
title: sub-s035_task-noisy_run-1_sbref.json

description: :unav
DOI: 10.57782/rzm27t/ovnahr
title: sub-s034_task-clean_run-1_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/onpere
title: sub-s035_task-noisy_run-2_events.tsv

description: :unav
DOI: 10.57782/rzm27t/vqljit
title: sub-s032_task-audiovisual_run-2_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/mhjphf
title: sub-s033_task-noisy_run-2_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/xtncjs
title: sub-s032_task-noisy_run-1_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/40dibn
title: sub-s033_task-audiovisual_run-1_sbref.json

description: :unav
DOI: 10.57782/rzm27t/nl79kr
title: sub-s034_task-noisy_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/1wq9jh
title: sub-s031_phasediff.json

description: :unav
DOI: 10.57782/rzm27t/zunflu
title: sub-s033_task-noisy_run-1_bold.json

description: :unav
DOI: 10.57782/rzm27t/dbf6qg
title: sub-s031_task-clean_run-2_events.tsv

description: :unav
DOI: 10.57782/rzm27t/gvi8lj
title: sub-s035_task-noisy_run-1_sbref.nii.gz

description: :unav
DOI: 10.5281/zenodo.5764172
title: Total Viewshed of Bohemia

description: The dataset represents a collection of total viewsheds (cf. Llobera et al. 2010) created for the territory of Bohemia (Czech Republic; ca. 57,000 km2). The total-viewshed calculation was based on the R2 algorithm (see Franklin and Ray 1994) and uses the viewshed function from MATLAB’s Mapping Toolbox that was significantly optimized by the authors for large-scale parallel computations. To reduce the computational time, we calculated single viewsheds using every fourth cell as the observing point (cf. Rášová 2017).


The Digital Terrain Model of the Czech Republic of the 5th Generation (DMR 5G) was used as input for the calculations. Prior to the calculation, the input DEM was cleared of modern landscape elements (e.g. embankments of railways and roads, quarries, etc.; for details see Novák – Pružinec 2022). Eight total visibility models of the territory of Bohemia were constructed using the IT4Innovations research infrastructure (https://www.it4i.cz/). Both the observer and the target heights were set at 1.5 m. The viewsheds differ in two parameters: the visibility radius and the resolution of the input grid. As the basic radius, we have set 0.5 km and the cell size of 5 m; further layers are conceived as multiples of these parameters: 1 km/10 m, 2 km/20 m, 4 km/40 m, 8 km/80 m, 16 km/160 m and 32 km/320 m. The only exception is the model with a radius of 64 km, where we preserved the cell size of the preceding iteration (320 m). In the individual models, the visibility values are indicated in percentages corresponding to the portion of visible cells in the given radius (0–100%; rounded up to the next complete value).


Filenames of individual rasters correspond to the parameters set above. For further details see:



	
Kuna, M. – Novák, D. – Bucha Rašová, A. – Bucha, B. – Machová, B. – Havlice, J. – John, J. – Chvojka, O. 2022: Computing and testing extensive total viewsheds: a case of prehistoric burial mounds in Bohemia. Journal of Archaeological Science 142, 105596. https://doi.org/10.1016/j.jas.2022.105596
	
Novák, D. – Pružinec, F. 2022: Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: http://dx.doi.org/10.2139/ssrn.4063514
description: This contribution was supported by the Archaeological Information System of the Czech Republic – Second Generation project (CZ.02.1.01/0.0/0.0/16_013/0001439), which is part of the OP VVV programme financed by the European Union and processed by the Ministry of Education, Youth and Sport of the CR. For the visibility calculation, we made use of the funding of the IT4Innovations infrastructure for the Total visibility of the Czech landscape project (OPEN-15-46).
DOI: 10.5281/zenodo.5764173
title: Total Viewshed of Bohemia

description: The dataset represents a collection of total viewsheds (cf. Llobera et al. 2010) created for the territory of Bohemia (Czech Republic; ca. 57,000 km2). The total-viewshed calculation was based on the R2 algorithm (see Franklin and Ray 1994) and uses the viewshed function from MATLAB’s Mapping Toolbox that was significantly optimized by the authors for large-scale parallel computations. To reduce the computational time, we calculated single viewsheds using every fourth cell as the observing point (cf. Rášová 2017).


The Digital Terrain Model of the Czech Republic of the 5th Generation (DMR 5G) was used as input for the calculations. Prior to the calculation, the input DEM was cleared of modern landscape elements (e.g. embankments of railways and roads, quarries, etc.; for details see Novák – Pružinec 2022). Eight total visibility models of the territory of Bohemia were constructed using the IT4Innovations research infrastructure (https://www.it4i.cz/). Both the observer and the target heights were set at 1.5 m. The viewsheds differ in two parameters: the visibility radius and the resolution of the input grid. As the basic radius, we have set 0.5 km and the cell size of 5 m; further layers are conceived as multiples of these parameters: 1 km/10 m, 2 km/20 m, 4 km/40 m, 8 km/80 m, 16 km/160 m and 32 km/320 m. The only exception is the model with a radius of 64 km, where we preserved the cell size of the preceding iteration (320 m). In the individual models, the visibility values are indicated in percentages corresponding to the portion of visible cells in the given radius (0–100%; rounded up to the next complete value).


Filenames of individual rasters correspond to the parameters set above. For further details see:



	
Kuna, M. – Novák, D. – Bucha Rašová, A. – Bucha, B. – Machová, B. – Havlice, J. – John, J. – Chvojka, O. 2022: Computing and testing extensive total viewsheds: a case of prehistoric burial mounds in Bohemia. Journal of Archaeological Science 142, 105596. https://doi.org/10.1016/j.jas.2022.105596
	
Novák, D. – Pružinec, F. 2022: Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: http://dx.doi.org/10.2139/ssrn.4063514
description: This contribution was supported by the Archaeological Information System of the Czech Republic – Second Generation project (CZ.02.1.01/0.0/0.0/16_013/0001439), which is part of the OP VVV programme financed by the European Union and processed by the Ministry of Education, Youth and Sport of the CR. For the visibility calculation, we made use of the funding of the IT4Innovations infrastructure for the Total visibility of the Czech landscape project (OPEN-15-46).
DOI: 10.57782/rzm27t/nijlco
title: sub-s032_task-rest_sbref.json

description: :unav
DOI: 10.57782/rzm27t/efj2kk
title: sub-s031_task-audiovisual_run-2_events.tsv

description: :unav
DOI: 10.57782/rzm27t/zsxzwv
title: sub-s031_task-audiovisual_run-1_events.tsv

description: :unav
DOI: 10.57782/rzm27t/0soek1
title: sub-s034_task-audiovisual_run-1_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/je7isd
title: sub-s032_phasediff.nii.gz

description: :unav
DOI: 10.57782/rzm27t/ktwn4r
title: sub-s033_task-noisy_run-2_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/hzhxd5
title: sub-s035_task-clean_run-1_events.tsv

description: :unav
DOI: 10.57782/rzm27t/9bnygw
title: sub-s033_task-noisy_run-1_events.tsv

description: :unav
DOI: 10.57782/rzm27t/kmzqw5
title: sub-s035_task-noisy_run-2_bold.json

description: :unav
DOI: 10.57782/rzm27t/igguyr
title: sub-s032_task-clean_run-2_events.json

description: :unav
DOI: 10.57782/rzm27t/13rccn
title: sub-s035_task-rest_sbref.nii.gz

description: :unav
DOI: 10.57782/rzm27t/bo5uwo
title: sub-s034_task-clean_run-1_bold.nii.gz

description: :unav
DOI: 10.57782/rzm27t/cpdbfc
title: sub-s032_phasediff.json

description: :unav
DOI: 10.57782/rzm27t/sl2q54
title: sub-s032_task-clean_run-1_events.json

description: :unav
DOI: 10.57782/rzm27t/s3tbyr
title: sub-s031_task-noisy_run-1_sbref.nii.gz

description: :unav
DOI: 10.25549/uschist-ouc110756039
title: Daily Trojan, vol. 23, no. 111, Mar 18, 1932

description: Southern California Daily Trojan, vol. 23, no. 111, March 18, 1932.
DOI: 10.25549/uschist-ouc110756029
title: Daily Trojan, vol. 23, no. 115, Mar 31, 1932

description: Southern California Daily Trojan, vol. 23, no. 115, March 31, 1932.
DOI: 10.25549/uschist-ouc110756043
title: Daily Trojan, vol. 23, no. 118, Apr 5, 1932

description: Southern California Daily Trojan, vol. 23, no. 118, April 5, 1932.
DOI: 10.25549/uschist-ouc110761303
title: Daily Trojan, vol. 20, no. 94, Mar 1, 1929

description: Southern California Daily Trojan, vol. 20, no. 94, March 1, 1929.
DOI: 10.25549/uschist-ouc110761315
title: Daily Trojan, vol. 20, no. 96, Mar 4, 1929

description: Southern California Daily Trojan, vol. 20, no. 96, March 4, 1929.
DOI: 10.25549/uschist-ouc110761372
title: Daily Trojan, vol. 20, no. 104, Mar 14, 1929

description: Southern California Daily Trojan, vol. 20, no. 104, March 14, 1929.
DOI: 10.25549/uschist-ouc110761394
title: Daily Trojan, vol. 20, no. 108, Mar 20, 1929

description: Southern California Daily Trojan, vol. 20, no. 108, March 20, 1929.
DOI: 10.25549/uschist-ouc110761380
title: Daily Trojan, vol. 20, no. 113, Apr 4, 1929

description: Southern California Daily Trojan, vol. 20, no. 113, April 4, 1929.
DOI: 10.25549/uschist-ouc110761402
title: Daily Trojan, vol. 20, no. 118, Apr 12, 1929

description: Southern California Daily Trojan, vol. 20, no. 118, April 12, 1929.
DOI: 10.25549/uschist-ouc110761418
title: Daily Trojan, vol. 20, no. 126, Apr 24, 1929

description: Southern California Daily Trojan, vol. 20, no. 126, April 24, 1929.
DOI: 10.25549/uschist-ouc110761414
title: Daily Trojan, vol. 20, no. 128, Apr 26, 1929

description: Southern California Daily Trojan, vol. 20, no. 128, April 26, 1929.
DOI: 10.25549/uschist-ouc110761454
title: Daily Trojan, vol. 20, no. 139, May 13, 1929

description: Southern California Daily Trojan, vol. 20, no. 139, May 13, 1929.
DOI: 10.25549/uschist-ouc110761440
title: Daily Trojan, vol. 20, no. 143, May 17, 1929

description: Southern California Daily Trojan, vol. 20, no. 143, May 17, 1929.
DOI: 10.25549/uschist-ouc110756641
title: Daily Trojan, vol. 25, no. 76, Feb 1, 1934

description: Southern California Daily Trojan, vol. 25, no. 76, February 1, 1934.
DOI: 10.25549/uschist-ouc110756633
title: Daily Trojan, vol. 25, no. 77, Feb 14, 1934

description: Southern California Daily Trojan, vol. 25, no. 77, February 14, 1934.
DOI: 10.15468/dl.ae2kfy
title: Occurrence Download

description: A dataset containing 13656 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sphingidae",
 "DatasetKey is Observation.org, Nature data from around the World",
 "Country is Germany",
 "Year is greater than or equal to 2025",
 "Year is less than or equal to 2026",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 13656 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033334-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/uschist-ouc110756631
title: Daily Trojan, vol. 25, no. 78, Feb 15, 1934

description: Southern California Daily Trojan, vol. 25, no. 78, February 15, 1934.
DOI: 10.25549/uschist-ouc110756651
title: Daily Trojan, vol. 25, no. 82, Feb 21, 1934

description: Southern California Daily Trojan, vol. 25, no. 82, February 21, 1934.
DOI: 10.25549/uschist-ouc110756683
title: Daily Trojan, vol. 25, no. 103, Mar 23, 1934

description: Southern California Daily Trojan, vol. 25, no. 103, March 23, 1934.
DOI: 10.25549/uschist-ouc110756271
title: Daily Trojan, vol. 24, no. 54, Nov 29, 1932

description: Southern California Daily Trojan, vol. 24, no. 54, November 29, 1932.
DOI: 10.25549/uschist-ouc110756317
title: Daily Trojan, vol. 24, no. 61, Dec 8, 1932

description: Southern California Daily Trojan, vol. 24, no. 61, December 8, 1932.
DOI: 10.25549/uschist-ouc110756313
title: Daily Trojan, vol. 24, no. 68, Jan 10, 1933

description: Southern California Daily Trojan, vol. 24, no. 68, January 10, 1933.
DOI: 10.25549/uschist-ouc110756283
title: Daily Trojan, vol. 24, no. 74, Jan 18, 1933

description: Southern California Daily Trojan, vol. 24, no. 74, January 18, 1933.
DOI: 10.25549/uschist-ouc110756319
title: Daily Trojan, vol. 24, no. 75, Jan 19, 1933

description: Southern California Daily Trojan, vol. 24, no. 75, January 19, 1933.
DOI: 10.25549/uschist-ouc110761519
title: Daily Trojan, vol. 21, no. 10, Sep 30, 1929

description: Southern California Daily Trojan, vol. 21, no. 10, September 30, 1929.
DOI: 10.25549/uschist-ouc110761569
title: Daily Trojan, vol. 21, no. 14, Oct 4, 1929

description: Southern California Daily Trojan, vol. 21, no. 14, October 4, 1929.
DOI: 10.25549/uschist-ouc110761527
title: Daily Trojan, vol. 21, no. 16, Oct 8, 1929

description: Southern California Daily Trojan, vol. 21, no. 16, October 8, 1929.
DOI: 10.25549/uschist-ouc110761577
title: Daily Trojan, vol. 21, no. 22, Oct 16, 1929

description: Southern California Daily Trojan, vol. 21, no. 22, October 16, 1929.
DOI: 10.15468/dl.n4gngt
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.29_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Capricornis milneedwardsii"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033335-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/uschist-ouc110761571
title: Daily Trojan, vol. 21, no. 32, Oct 30, 1929

description: Southern California Daily Trojan, vol. 21, no. 32, October 30, 1929.
DOI: 10.25549/uschist-ouc110756281
title: Daily Trojan, vol. 24, no. 80, Feb 7, 1933

description: Southern California Daily Trojan, vol. 24, no. 80, February 7, 1933.
DOI: 10.25549/uschist-ouc110756305
title: Daily Trojan, vol. 24, no. 82, Feb 9, 1933

description: Southern California Daily Trojan, vol. 24, no. 82, February 9, 1933.
DOI: 10.25549/uschist-ouc110756359
title: Daily Trojan, vol. 24, no. 87, Feb 16, 1933

description: Southern California Daily Trojan, vol. 24, no. 87, February 16, 1933.
DOI: 10.25549/uschist-ouc110756385
title: Daily Trojan, vol. 24, no. 92, Feb 24, 1933

description: Southern California Daily Trojan, vol. 24, no. 92, February 24, 1933.
DOI: 10.25549/uschist-ouc110756379
title: Daily Trojan, vol. 24, no. 102, Mar 10, 1933

description: Southern California Daily Trojan, vol. 24, no. 102, March 10, 1933.
DOI: 10.25549/uschist-ouc110761583
title: Daily Trojan, vol. 21, no. 42, Nov 14, 1929

description: Southern California Daily Trojan, vol. 21, no. 42, November 14, 1929.
DOI: 10.25549/uschist-ouc110761697
title: Daily Trojan, vol. 21, no. 59, Dec 13, 1929

description: Southern California Daily Trojan, vol. 21, no. 59, December 13, 1929.
DOI: 10.25549/uschist-ouc110755156
title: Daily Trojan, vol. 21, no. 60, Jan 3, 1930

description: Southern California Daily Trojan, vol. 21, no. 60, January 3, 1930.
DOI: 10.25549/uschist-ouc110755036
title: Daily Trojan, vol. 21, no. 69, Jan 16, 1930

description: Southern California Daily Trojan, vol. 21, no. 69, January 16, 1930.
DOI: 10.25549/uschist-ouc110755026
title: Daily Trojan, vol. 21, no. 70, Jan 17, 1930

description: Southern California Daily Trojan, vol. 21, no. 70, January 17, 1930.
DOI: 10.25549/uschist-ouc110756677
title: Daily Trojan, vol. 25, no. 104, Apr 2, 1934

description: Southern California Daily Trojan, vol. 25, no. 104, April 2, 1934.
DOI: 10.25549/uschist-ouc110756707
title: Daily Trojan, vol. 25, no. 108, Apr 6, 1934

description: Southern California Daily Trojan, vol. 25, no. 108, April 6, 1934.
DOI: 10.25549/uschist-ouc110756713
title: Daily Trojan, vol. 25, no. 118, Apr 20, 1934

description: Southern California Daily Trojan, vol. 25, no. 118, April 20, 1934.
DOI: 10.5281/zenodo.18718498
title: TomatoLite Dataset for Object Detection

description: # Tomato Dataset


## Overview

This repository provides the dataset used in our paper:

**"Lightweight Tomato Disease Detection in Complex Field Environments based on Improved YOLOv8"**.


The dataset contains field images of tomato plants collected under real-world conditions (varying illumination, occlusion, cluttered backgrounds). Annotations are provided in **YOLO** format and (optionally) **Pascal VOC** format for reproducibility.


> IMPORTANT: Train/val splits are provided and should be used as-is to reproduce the paper results.


## Task

- **Task type**: Object detection

- **Target**: Tomato disease/pest symptoms on leaves (bounding boxes)


## Classes

The class index-to-name mapping is provided in:

- `yolo/Labels.txt`


Please ensure your training code uses the exact same class ordering.