Corona KH-4B Research Articles

Long-term gully dynamics over cropland in the black soil area of China based on systematic sampling

Understanding the large-scale spatial distribution characteristics of gully development dynamics, particularly over long periods, can help in accurately identifying areas with severe gully erosion and is thus crucial for targeted gully prevention and rehabilitation efforts. This study aimed to investigate the long-term dynamics of permanent gullies on cropland in the Songnen typical black soil region (SBR), which is the most important commercial grain production area in China, covering an area of 212,000 km2. For this purpose, 998 sampling units were selected using the systematic sampling method. Based on Corona KH-4B images from 1970 and Google images from 2018, all gullies within each sampling unit were visually interpreted. In the past 50 years, the number of permanent gullies on cropland in SBR increased by 24.55 %, but the average linear density of gullies in the cropland sampling unit decreased from 0.47 to 0.45 km·km−2 because the average lengths of gullies decreased from 285.90 m to 233.15 m. While 50.50 % of gullies found in 1970 disappeared from the images of 2018, more gullies formed and were widespread in the east part of the study area characterized by a topography of rolling hills. In particular, 66.70 % of gullies were active, including all newly formed gullies and 16.28 % of long-standing gullies (LSGs), and the average gully retreat rate of LSGs was 0.53 m·yr−1, with active LSGs grew at a rate of 3.26 m·yr−1 on average, indicating the severity of gully erosion and limited effectiveness of efforts made to control gully erosion in the black soil region of China. The threat of gully erosion is more serious in the eastern part of SBR, with 44.69 % of cropland suffering gully erosion and 66.14 % of the gullies being active. Moreover, the trend of increased gully erosion in the centre and the west requires further attention. The findings highlight the need for studies on more effective and targeted measures for gully control and their wide application in order to ensure the sustainable utilization of the valuable black soil resources.

2OC: A General Automated Orientation and Orthorectification Method for Corona KH-4B Panoramic Imagery

Due to a lack of geographical reference information, complex panoramic camera models, and intricate distortions, including radiation, geometric, and land cover changes, it can be challenging to effectively apply the large number (800,000+) of high-resolution Corona KH-4B panoramic images from the 1960s and 1970s for surveying-related tasks. This limitation hampers their significant potential in the remote sensing of the environment, urban planning, and other applications. This study proposes a method called 2OC for the automatic and accurate orientation and orthorectification of Corona KH-4B images, which is based on generalized control information from reference images such as Google Earth orthophoto. (1) For the Corona KH-4B panoramic camera, we propose an adaptive focal length variation model that ensures accuracy and consistency. (2) We introduce a robust multi-source remote sensing image matching algorithm, which includes an accurate primary orientation estimation method, a multi-threshold matching enhancement strategy based on scale, orientation, and texture (MTE), and a model-guided matching strategy. These techniques are employed to extract high-accuracy generalized control information for Corona images with significant geometric distortions and numerous weak texture areas. (3) A time-iterative Corona panoramic digital differential correction method is proposed. The orientation and orthorectification results of KH-4B images from multiple regions, including the United States, Russia, Austria, Burkina Faso, Beijing, Chongqing, Gansu, and the Qinghai–Tibet Plateau in China, demonstrate that 2OC not only achieves automation but also attains a state-of-the-art level of generality and accuracy. Specifically, the standard deviation of the orientation is less than 2 pixels, the mosaic error of orthorectified images is approximately 1 pixel, and the standard deviation of ground checkpoints is better than 4 m. In addition, 2OC can provide a longer time series analysis of data from 1962 to 1972, benefiting various fields such as environmental remote sensing and archaeology.

An integrated deep learning and object-based image analysis approach for mapping debris-covered glaciers

Evaluating glacial change and the subsequent water stores in high mountains is becoming increasingly necessary, and in order to do this, models need reliable and consistent glacier data. These often come from global inventories, usually constructed from multi-temporal satellite imagery. However, there are limitations to these datasets. While clean ice can be mapped relatively easily using spectral band ratios, mapping debris-covered ice is more difficult due to the spectral similarity of supraglacial debris to the surrounding terrain. Therefore, analysts often employ manual delineation, a time-consuming and subjective approach to map debris-covered ice extents. Given the increasing prevalence of supraglacial debris in high mountain regions, such as High Mountain Asia, a systematic, objective approach is needed. The current study presents an approach for mapping debris-covered glaciers that integrates a convolutional neural network and object-based image analysis into one seamless classification workflow, applied to freely available and globally applicable Sentinel-2 multispectral, Landsat-8 thermal, Sentinel-1 interferometric coherence, and geomorphometric datasets. The approach is applied to three different domains in the Central Himalayan and the Karakoram ranges of High Mountain Asia that exhibit varying climatic regimes, topographies and debris-covered glacier characteristics. We evaluate the performance of the approach by comparison with a manually delineated glacier inventory, achieving F-score classification accuracies of 89.2%–93.7%. We also tested the performance of this approach on declassified panchromatic 1970 Corona KH-4B satellite imagery in the Manaslu region of Nepal, yielding accuracies of up to 88.4%. We find our approach to be robust, transferable to other regions, and accurate over regional (>4,000 km2) scales. Integrating object-based image analysis with deep-learning within a single workflow overcomes shortcomings associated with convolutional neural network classifications and permits a more flexible and robust approach for mapping debris-covered glaciers. The novel automated processing of panchromatic historical imagery, such as Corona KH-4B, opens the possibility of exploiting a wealth of multi-temporal data to understand past glacier changes.

An integrated approach to modelling the interaction of the natural landscape and the karez water system in Turpan (Xinjiang, P.R.C.)

The research in this paper focusses on examining the link between the karez and their location in the physical landscape. The landscape can be divided into specific classes dependent on their natural characteristics, such as slope, drainage, and soil properties. These classes are compared to the known karez locations, settlement, and vegetation throughout time using Corona KH4B-, Landsat 8-, and Pleiades 1-imagery. It is shown that the karez are indeed restricted to certain landscape types, nonetheless, variety is still possible within one site location. When including settlement patterns, they are heavily influenced by the presence of karez and/or surface water. The connection between the landscape classes, the karez, and the settlements is evident but interestingly some aspects cannot be explained fully by the physical surroundings only. This leads to believe that other agents must also be present of socio-economical, mental, or historical nature.

Regional-Scale Systematic Mapping of Archaeological Mounds and Detection of Looting Using COSMO-SkyMed High Resolution DEM and Satellite Imagery

“Tells” are archaeological mounds formed by deposition of large amounts of anthropogenic material and sediments over thousands of years and are the most important and prominent features in Near and Middle Eastern archaeological landscapes. In the last decade, archaeologists have exploited free-access global digital elevation model (DEM) datasets at medium resolution (i.e., up to 30 m) to map tells on a supra-regional scale and pinpoint tentative tell sites. Instead, the potential of satellite DEMs at higher resolution for this task was yet to be demonstrated. To this purpose, the 3 m resolution imaging capability allowed by the Italian Space Agency’s COSMO-SkyMed Synthetic Aperture Radar (SAR) constellation in StripMap HIMAGE mode was used in this study to generate DEM products of enhanced resolution to undertake, for the first time, a systematic mapping of tells and archaeological deposits. The demonstration is run at regional scale in the Governorate of Wasit in central Iraq, where the literature suggested a high density of sites, despite knowledge gaps about their location and spatial distribution. Accuracy assessment of the COSMO-SkyMed DEM is provided with respect to the most commonly used SRTM and ALOS World 3D DEMs. Owing to the 10 m posting and the consequent enhanced observation capability, the COSMO-SkyMed DEM proves capable to detect both well preserved and levelled or disturbed tells, standing out for more than 4 m from the surrounding landscape. Through the integration with CORONA KH-4B tiles, 1950s Soviet maps and recent Sentinel-2 multispectral images, the expert-led visual identification and manual mapping in the GIS environment led to localization of tens of sites that were not previously mapped, alongside the computation of a figure as up-to-date as February 2019 of the survived tells, with those affected by looting. Finally, this evidence is used to recognize hot-spot areas of potential concern for the conservation of tells. To this purpose, we upgraded the spatial resolution of the observations up to 1 m by using the Enhanced Spotlight mode to collect a bespoke time series. The change detection tests undertaken on selected clusters of disturbed tells prove how a dedicated monitoring activity may allow a regular observation of the impacts due to anthropogenic disturbance (e.g., road and canal constructions or ploughing).

Remote Sensing-Based Analysis of Urban Landscape Change in the City of Bucharest, Romania

The paper investigates the urban landscape changes for the last 50 years in Bucharest, the capital city of Romania. Bucharest shows a complex structural transformation driven by the socialist urban policy, followed by an intensive real-estate market development. Our analysis is based on a diachronic set of high-resolution satellite imagery: declassified CORONA KH-4B from 1968, SPOT-1 from 1989, and multisensor stacked layers from Sentinel-1 SAR together with Sentinel-2MSI from 2018. Three different datasets of land cover/use are extracted for the reference years. Each dataset reveals its own urban structure pattern. The first one illustrates a radiography of the city in the second part of the 20th century, where rural patterns meet the modern ones, while the second one reveals the frame of a city in a full process of transformation with multiple constructions sites, based on the socialist model. The third one presents an image of a cosmopolitan city during an expansion process, with a high degree of landscape heterogeneity. All the datasets are included in a built-up change analysis in order to map and assess the spatial transformations of the city pattern over 5 decades. In order to quantify and map the changes, the Built-up Change Index (BCI) is introduced. The results highlight a particular situation linked to the policy development visions for each decade, with major changes of about 50% for different built-up classes. The GIS analysis illustrates two major landscape transformations: from the old semirural structures with houses surrounded by gardens from 1968, to a compact pattern with large districts of blocks of flats in 1989, and a contemporary city defined by an uncontrolled urban sprawl process in 2018.

Glacier mapping and change analysis in Chandra basin, Western Himalaya, India during 1971–2016

ABSTRACT For carrying out glacier change analysis in Chandra basin, Western Himalaya, India during 1971–2016, glacier inventory is generated for year 2002 using Landsat Enhanced Thematic Mapper+ (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2) data. Total 395 glaciers are mapped covering 703.3 ± 20.4 km2 area with minimum glacier size being >0.02 km2. Out of these, 59 glaciers have debris-covered ice covering an area of 67.2 ± 1.9 km2. In this study, a subset of 169 glaciers is used for glacier area change analysis using Corona KH-4B (1971), Landsat ETM+ (2002) and Sentinel-2 (2016) images due to the availability of cloud free data sources. In 1971, 639.4 ± 5.8 km2 glacier area is estimated which decreased to 620.2 ± 18.0 km2 (–3.0 ± 3.0%) in 2002 and 608.1 ± 10.3 km2 (–4.9 ± 1.9%) in 2016. The change in glacier length of Samudra Tapu and Gepang Gath glaciers is showing increasing trend since last two decades as compared to Hamtah, Chhota Shigri and Bara Shigri glaciers due to presence of pro-glacial lake at their snout. Clean-ice glaciers, glaciers with low mean elevation, glaciers having steep surface, glaciers with west to south and east to south orientation, small size glaciers and glaciers having pro-glacial lake at the snout are responsible to higher loss in glacier area. Statistical trend analysis using Mann-Kendall test and Sen’s slope estimator test show that Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) based annual mean temperature have rising trend at a rate of 0.02°C per year during 1961–2015, and can be ascribed as one of the factors for glacier shrinking.

Sonapani Glacier Recession over a Century from 1906-2016, Chandra Basin, Himachal Himalaya

Abstract In this study, the changes in snout and area of Sonapani glacier located in Chandra river valley, Himachal Himalaya has been studied over a century from 1906 to 2016. The study used a Survey Map (1906), Corona KH4-B (1971), Landsat 5 TM (1989), Landsat 7 ETM+ (2000) and Google Earth (2016) data images. In order to validate the satellite data images and other field studies, field work was carried out during 2014 in this area. The Survey Map (SM) of the Glacier was prepared by the Geological Survey of India (GSI) in 1906 and hence, demarcated its earliest snout position. Thus, the SM has been used as the base map for overall change detection studies. The study indicated a total glacier retreat of 1820 m at a rate of 16.5 ma−1 over a time period of century from 1906 to 2016. During the different time intervals, the SG has indicated variable recessional patterns. For instance, the glacier has retreated by 991 m at a rate of 15 ma−1 during 1906-1971, 202 m at a rate of 11.2 ma−1 during1971-1989, 31 m at a rate 2.8 ma−1 during 1989-2000 and 596 m at rate of 37.3 ma−1 during 2000-2016. During the recent time period from 2000 to 2016, the rate of recession has increased rapidly. Due to this rapid recession of the glacier a major tributary towards the lower left side has also detached from it. The glacier also indicated an area loss of 29.7% (6.85 km2) from 1906 (23.9 km2) to 2016 (17.09 km2).

Mountain Arable Land Abandonment (1968–2018) in the Romanian Carpathians: Environmental Conflicts and Sustainability Issues

The agricultural mountain landscape in the Romanian Carpathians follows the same change trend in other European mountains, from variety and individuality to simplification and uniformization. Our paper proposes two complementary case studies from the Southern Carpathians—Poiana Mărului and Fundata, representative areas for the entire Carpathian ecoregion. The research focuses on a remote sensing approach with Corona KH-4B (1968) and Planet Scope (2018) images at 2.0–3.0 m resolution used for mapping arable plots pattern and size change. Landscape transformation modelling is focused on four-hectare sampled grid for both case study areas, followed by a landscape metric analysis. Fundata area is the most transformed, where arable plots disappeared under the service-based economy pressure. Poiana Mărului shows an earlier stage of landscape transformation, where the arable land abandonment process is incipient. The spatial and statistical analysis and field survey confirmed that tourism changed the traditional agricultural landscape, generating potential environmental conflicts and indicating the sustainability degree.

Evolution of a debris-covered glacier in the western Himalaya during the last four decades (1971–2016): A multiparametric assessment using remote sensing and field observations

This study assesses the response of the Panchi Nala glacier, Bhaga Basin, western Himalaya to climate change by monitoring multiple glacier parameters namely, length, area, debris cover, snowline altitude (SLA), surface ice velocity (SIV), and surface elevation change (Δh). These parameters were analysed using high-resolution satellite images (Corona KH-4B and Sentinel-2 MSI) and medium-resolution ones (Landsat TM/ETM+/OLI and Terra ASTER) acquired between 1971 and 2016, along with extensive field observations. Considering only dimensional changes, the glacier appears to have low rates of recession (4.54 ± 2.56 m y−1) and deglaciation (0.11 ± 0.04% y−1) over the study period (1971–2016). However, SIV and Δh values reveal a significant slowdown (33.87%; 1992/93–2015/16), and an extensive lowering (−1.62 ± 0.06 m y−1; 2000–2013) on the glacier. The debris cover area and SLA also increased by 23.50 ± 1.74% and 287.63 m, respectively, during 1971–2016. Increase in the mean winter minimum temperature, and decrease in the winter snowfall are probably the main drivers of glacier depletion. We conclude that the significant slowdown, extensive surface lowering, development of a proglacial lake and appearance of the supraglacial lakes collectively indicate a severe glacier degeneration. This forewarns that the glacier may experience an accelerated pace of wastage in the future.

Semi-automatic extraction and mapping of dyke swarms based on multi-resolution remote sensing images: Applied to the dykes in the Kuluketage region in the northeastern Tarim Block

The geometry and spatial distribution of mafic dyke swarms provide information about geodynamics. However, mapping large-scale dyke swarms manually is a time-consuming and expensive process. Here we present an efficient method to map dyke swarms semi-automatically by using multi-resolution remote sensing images. This method is applied in the Kuluketage region in the northeastern Tarim Block, northwest China where mafic dykes of multiple trends are widely exposed and with the dominant NW trend being of probable Neoproterozoic age. The tracing of dykes, including their orientation, length, thickness, density, and distribution is done by integrating 30-m multispectral Landsat 8 and 2-m panchromatic CORONA KH-4B imagery. The Gramm-Schmidt Spectral Sharpening approach is used to generate color composite and fusion images with 2-m resolution. The Canny edge detector and Hough transform are used to detect dyke edges. Combining the detection of dyke edges with ArcGIS™, the dyke orientation, length, density, thickness, and exposed area are measured. The accuracy of the semi-automatic method exceeds 75% in comparison with manual mapping of the dykes in the Kuluketage region.

Regional Geomorphological Conditions Related to Recent Changes of Glacial Lakes in the Issyk-Kul Basin, Northern Tien Shan

To assess the current state of glacial lakes, we examine the seasonal lake-area changes of 339 glacial lakes in the Teskey and Kungoy Ranges of the Issyk-Kul Basin, Kyrgyzstan, during 2013–2016 based on optical satellite images (Landsat7/ETM+ and 8/OLI). The glacial lakes are classified into six types based on their seasonal variations in area: stable, increasing, decreasing, appearing, vanishing, and short-lived. We then track the number of each type in a given year and examine how each number changes from one year to the next. We find that many appearing, vanishing, and short-lived types occurred in both mountain ranges, having a large variability in number that is not directly related to the local short-term summer temperature anomaly, nor to precipitation or glacier recession. However, those in the Teskey Range vary significantly more than those in the Kungoy Range. To determine if the changing number and distribution of the various lake types may be due to changes in ground ice, we apply differential interferometric synthetic aperture radar (DInSAR) analysis using ALOS-2/PALSAR-2 for the debris landforms behind which glacial lakes appear. In the Teskey Range, ground ice occurs in 413 out of a total of 930 debris landforms, whereas in the Kungoy Range, ground ice occurs in 71 out of 180. In zones with predominant glacier-retreat during 1971–2010 (from Corona KH-4B and ALOS/PRISM), the Teskey Range had 180 new lake depressions as potential lake-basins, whereas the Kungoy Range had just 22. Existing depressions also expanded when melting ice produced subsidence. Such subsidence, together with debris landforms containing ground ice and ice tunnels, appear to cause the observed large number variability. In particular, the deposition of ice and debris by tunnel collapse or the freezing of storage water in a debris landform may close-off an ice tunnel, causing a lake to appear. Subsequent re-opening via melting of such blockage would produce either a vanishing or a short-lived type. In this way, the large variability in the number of each lake type and the distribution of types over this four-year period arises from regional geomorphological conditions and not directly from the local short-term summer temperature anomaly and precipitation or glacier recession.

Frontal recession of Parkachik Glacier between 1971-2015, Zanskar Himalaya using remote sensing and field data

Parkachik Glacier is located in the Suru sub-basin of the Upper Indus River, Zanskar Himalaya. The Glacier has been analysed using Corona KH-4B (1971), Landsat-TM (1999), field survey (2015), Google EarthTM (2015) and ASTER GDEM (2015) for frontal recession and area changes. Overall, from 1971 to 2015, the Glacier has retreated by 127 ± 0.09 m i.e. (0.75 ± 0.07%) at a rate of 2.9 ± 0.004 ma−1 with a simultaneous decrease in area from 49.5 to 48.8 km2 i.e. 740 ± 0.7 m2 (1.5 ± 0.09%) at a rate of 74 ± 0.7 m2a−1. However, during recent decade (1999–2015), the rate of glacier recession of 3.9 ± 0.004 ma−1 with a corresponding area loss of 500 ± 0.74m2 (1 ± 0.1%) was higher than the retreat rate of 2.3 ± 0.001 ma−1 and an area loss of 240 ± 0.02m2 (0.48 ± 0.08%) during 1971–1999. In the field, the evidences of glacier recession are present in the form of separated dead ice blocks from the main Glacier, recessional dumps/moraines, active ice calving activity and a small proglacial pond/lake at the terminus/snout of the Glacier. However, the recession over the studied period has been very slow and is controlled by its topographic configuration, particularly the large altitudinal range (6030–3620 m), almost northerly aspect and steep slope (average ~ 30°).

High Resolution Landscape Change Analysis with CORONA KH-4B Imagery. A Case Study from Iron Gates Reservoir Area

Mapping landscape change at detailed scales is an interesting task when the focus is not only the land cover change. The paper proposes the integration of a diachronic imagery set in a GIS application in order to obtain precise maps of the key qualitative changes along a representative sector of the Danube River Defile where the Iron Gates emerged between 1965-1972 to the border between Romania and Serbia. A photogrammetric process approach was developed for the building of precise historical orthophoto coverage on the basis of a CORONA KH-4B/ DECLASS-1 dataset. This was focused on reconstructing the image geometry and building a precise orientation, together with an aerial triangulation operation. The results were a Digital Surface Model and an orthophoto (about 5 m average geometric accuracy). This data was integrated into a GIS project with vector data extracted from the latest orthophotos (0.5 m, by ANCPI Bucharest) for mapping of landscape changes as an effect of the complex hydrotechnical works. The Iron Gates reservoir level was of about +33 m higher at the beginning of the 1970s in comparison with the primary Danube River level, the road and the railroad moved upslope like Orşova town and other villages. The most dramatic change was related to the total flooding of Ada-Kaleh Island with a Turkish settlement and a Vauban system fortress, an interesting historical and cultural site.

Thermokarst Lake Changes in the Southern Fringe of Siberian Permafrost Region in Mongolia Using Corona, Landsat, and ALOS Satellite Imagery from 1962 to 2007

This study presents thermokarst lake changes at seven different sites in the continuous and isolated permafrost zones in Mongolia. Lakes larger than 0.1 ha were analyzed using Corona KH-4, KH-4A and KH-4B (1962-1968), Landsat ETM + (1999-2001), and ALOS/AVNIR-2 (2006-2007) satellite imagery. Between 1962 and 2007, the total number and area of lakes increased by +21% (347 to 420), and +7% (3680 ha to 3936 ha) in the continuous permafrost zone, respectively. These changes correspond to the appearance of 85 new lakes (166 ha) during the last 45 years. In contrast, lakes in the isolated permafrost zone have decreased by –42% (118 to 68) in number and –12% (422 ha to 371 ha) in area from 1962 to 2007. The changes in lake area and number are likely attributed to shifts in climate regimes and local permafrost conditions. Since 1962, the mean annual air temperature and potential evapotranspiration have increased significantly in the northern continuous permafrost zone compared to the southern isolated permafrost zone. Due to ongoing atmospheric warming without any significant trend in annual precipitation, patches of ice-rich subsurface have thawed, and the number and area of lakes have accordingly developed in the continuous permafrost zone. Shrinking of thermokarst lakes in the isolated permafrost zone may be due to disappearing permafrost, deepening of the active layer, and increased water loss through surface evaporation and subsurface drainage.

Glacier changes in the Ravi basin, North-Western Himalaya (India) during the last four decades (1971–2010/13)

A glacier inventory of the Ravi basin, north-western Himalaya has been generated for the year 2002 using Landsat ETM+ and ASTER Global DEM (GDEM V2) as the baseline data for the change analysis. The Ravi basin consists of 285 glaciers (>0.02km2) covering an area of 164.5±7.5km2, including 71 debris-covered glaciers with an area of 36.1±2.1km2 (22% of total glacierized area) in 2002. Change analysis based on Corona KH-4B (1971), Worldview (2010) and Landsat 8 OLI/TRIS (2013) images was restricted to a subset of 157 glaciers (covering an area of 121.4±5.4km2 in 2002) due to cloud cover. Glacier area decreased from 125.8±1.9km2 (1971) to 119.9±4.8km2 (2010/13), a loss of 4.7±4.1% or 0.1±0.1%a−1. The glacier recession rate has decreased, to a minimum for the recent decades (2002–2010/13). The debris-covered glacier area increased by 19.2±2.2% (0.5±0.05%a−1) in the Ravi basin. However, there were significant variation in its sub-basins i.e. in Budhil and Upper Ravi sub-basin, where the debris-covered area increased by 28.6±3.1% (0.7±0.1%a−1) and 14±1.6% (0.3±0.04%a−1), respectively, between 1971 and 2010/13. Field investigation of selected glaciers (2010–2014) supports glacier recession trend from remote sensing data. Glacier retreat rates in the Ravi basin were lower than previously reported for selected glaciers in the similar basin and other basins (e.g. Chenab, Beas, Parbati, Baspa and Tirungkhad) of the Himachal Himalaya.

CORONA Photographs in Monsoonal Semi‐arid Environments: Addressing Archaeological Surveys and Historic Landscape Dynamics over North Gujarat, India

AbstractHere we illustrate a ground map approach that uses orthorectified CORONA KH4B images and declassified topographical maps to study historical land‐use dynamics and to help planning archaeological survey in the monsoonal semi‐arid alluvial plains of North Gujarat, India. In spite of its generalized use in archaeological applications, CORONA photographs have rarely been used in Indian archaeological contexts. The methods discuss a cost‐effective and integrated protocol for: (i) obtaining ground control points (GCPs) and orthorectify CORONA photographs when very high‐resolution imagery or detailed topographic maps are not available; and (ii) evaluating the integration of declassified datasets into Google Earth Pro for addressing archaeological surveys in remote areas. The merging of CORONA imagery with declassified USA and the former USSR historical military maps provided a picture of the human–environment interaction in North Gujarat of the past 40 years, prior to the intense development of mechanical agriculture and regional irrigation channels. We conclude by identifying the human and climate‐induced taphonomical processes that are obliterating a fragile landscape characterized by archaeological scatters located in fossilized sand dunes. Copyright © 2014 John Wiley & Sons, Ltd.

Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), P. R. China

Abstract. Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August–September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata) at Gaoqiao. Despite limitations such as geometric distortion and single panchromatic band, the 42 yr old Corona declassified images are invaluable for land-use/cover change detections when compared to recent satellite data sets.

Multitemporal High-Resolution Satellite Images for the Study and Monitoring of an Ancient Mesopotamian City and its Surrounding Landscape: The Case of Ur

The paper concerns the use of multitemporal high-resolution satellite images for the study of the ancient city of Ur, in southern Mesopotamia, inaccessible to scholars from 2003. The acquired dataset is composed by two Gambit KH-7 (1966) and one Corona KH-4B (1968) declassified spy space photos and by few images taken by the recent satellites for civilian use QuickBird-2 (2002, 2004, 2007), Ikonos-2 (2008), and WorldView-1 (2008). The processing of all these images and the integration with ASTER and SRTM DEMs allowed the acquisition of new data about the topographical layout of the city and its monuments and ancient roads; the georeferencing of all archaeological remains and traces visible on the images allowed the upgrade of the archaeological map of Ur. The research also provided important data concerning the reconstruction of the surrounding landscape, where a lot of traces of old channels and riverbeds of the Euphrates were identified in areas much modified and altered during the last decades by urbanization and agricultural works. Moreover, the multitemporal images allowed the monitoring of the conservation of the archaeological area, particularly before and after second Gulf War.

Modelling the acquisition times of CORONA satellite photographs: accuracy and application

In contrast to modern satellite images, information regarding the time of acquisition of declassified CORONA satellites is not readily available and requires access to hard-copy frame ephemeris data held by the US National Archives and Records Administration (NARA). In this article, the accuracy of a method described previously (Fowler 2006) for estimating the acquisition times of CORONA photographs using freely available historical Two Line Element orbital ephemeris data together with a commercial off-the-shelf modelling package for satellite operations has been investigated. The Root Mean Square Error (RMSE) between the modelled and documented acquisition times for a sample of 21 frames acquired by four CORONA KH-4B missions was determined to be of the order of 20.3 s and indicates that the approach can be used to estimate the acquisition times of CORONA satellite photographs to a relatively high degree of accuracy. From this, the solar azimuth and elevation for particular locations covered by the photographs can be readily determined. An example of the application of the technique is given for the case of two CORONA photographs of the landscape around the Roman siege-works at the fortress at Masada, Israel, and where knowledge of the solar lighting conditions at the time of acquisition enables the appearance of the archaeological features in their landscape setting to be appreciated. Being quick and low cost, this modelling approach has a broader utility for studies where knowledge of the acquisition times of CORONA satellite photographs is required.