The counter-intelligence service of the German Armed Forces High Command launched Operation Dora in 1941 to update terrain information of North Africa for the German warfare and to reconnoitre the frontier between Libya and Chad. This article presents Sonderkommando Dora as an example of military geoscientific reconnaissance during World War II in the North African theatre of war where the German Armed Forces needed more accurate military geographic information on the Western Desert, The scientific personnel comprised geographers, cartographers, geologists, astronomers, meteorologists and road specialists, and they prepared special maps on the environmental setting of the Libyan Sahara. As far as it is known, these special maps were never used by Axis troops (who fought in World War II against the Allies) for tactical purposes – although it cannot be ruled out that the maps provided general information on the proximity of the German Africa Corps, the Panzer Group Africa and of the Panzer Army Africa, respectively, and also of the retreating Army Group Africa.
{"title":"Sonderkommando Dora – Special Military Geoscientific Unit of the German Counter-Intelligence Sevice in North Africa 1942","authors":"H. Häusler","doi":"10.5787/46-1-1224","DOIUrl":"https://doi.org/10.5787/46-1-1224","url":null,"abstract":"The counter-intelligence service of the German Armed Forces High Command launched Operation Dora in 1941 to update terrain information of North Africa for the German warfare and to reconnoitre the frontier between Libya and Chad. This article presents Sonderkommando Dora as an example of military geoscientific reconnaissance during World War II in the North African theatre of war where the German Armed Forces needed more accurate military geographic information on the Western Desert, The scientific personnel comprised geographers, cartographers, geologists, astronomers, meteorologists and road specialists, and they prepared special maps on the environmental setting of the Libyan Sahara. As far as it is known, these special maps were never used by Axis troops (who fought in World War II against the Allies) for tactical purposes – although it cannot be ruled out that the maps provided general information on the proximity of the German Africa Corps, the Panzer Group Africa and of the Panzer Army Africa, respectively, and also of the retreating Army Group Africa.","PeriodicalId":53024,"journal":{"name":"Scientia Militaria","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84199205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Examples of castles and fortresses seen in publicly available LiDAR data by the national mapping agencies in Finland, the Netherlands, Norway, Slovenia, the United Kingdom, and United States demonstrate the value of LiDAR data for understanding military history. The data sets, which include derived grids and the original point clouds with densities from 2–24 points/m², always identify the ground points, generally include LiDAR return intensity values, and sometimes include point classifications that discriminate vegetation and buildings. Grids with 0,5- or one-metre resolution could be created from the highest density point clouds in this study, while grids with one- or two-metre resolution can be created from the lowest density clouds. The digital surface model, which includes everything seen by the sensor, notably ground, buildings, and vegetation, can be created with higher resolution than the bare earth grids. The surface model provides the best visual representation of the castle and its surroundings. Viewed in interactive 3D, the data allows familiarisation with the landscape. Optimal displays depend on the desired scale and the terrain characteristics, but hillshade or shaded reflectance maps, reverse greyscale slope maps, and openness maps all work effectively. Further analysis may include functions such as viewsheds, which enhance the understanding of key terrain.
{"title":"Castles in the Clouds: LiDAR for Historical Study and Terrain Analysis","authors":"P. Guth","doi":"10.5787/46-1-1226","DOIUrl":"https://doi.org/10.5787/46-1-1226","url":null,"abstract":"Examples of castles and fortresses seen in publicly available LiDAR data by the national mapping agencies in Finland, the Netherlands, Norway, Slovenia, the United Kingdom, and United States demonstrate the value of LiDAR data for understanding military history. The data sets, which include derived grids and the original point clouds with densities from 2–24 points/m², always identify the ground points, generally include LiDAR return intensity values, and sometimes include point classifications that discriminate vegetation and buildings. Grids with 0,5- or one-metre resolution could be created from the highest density point clouds in this study, while grids with one- or two-metre resolution can be created from the lowest density clouds. The digital surface model, which includes everything seen by the sensor, notably ground, buildings, and vegetation, can be created with higher resolution than the bare earth grids. The surface model provides the best visual representation of the castle and its surroundings. Viewed in interactive 3D, the data allows familiarisation with the landscape. Optimal displays depend on the desired scale and the terrain characteristics, but hillshade or shaded reflectance maps, reverse greyscale slope maps, and openness maps all work effectively. Further analysis may include functions such as viewsheds, which enhance the understanding of key terrain.","PeriodicalId":53024,"journal":{"name":"Scientia Militaria","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84161859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：