Reflections on Arno Peters (1916–2002)

Abstract

This paper describes a methodology for evaluating the planimetric accuracy of three US Civil War maps using GIS and spatial analytical techniques. The case-study is the Battle of Stones River in Tennessee and, in particular, maps depicting the events of December 31, 1862. An examination of the objectives, limitations and techniques employed by the topographer engineers who created the maps provides focus for the quantitative analysis and establishes the historical context needed to understand how and why the maps were constructed. The paper shows how GIS and spatial analysis can be utilized to document vanishing historic landscapes and reconstructing where certain historical events took place.     

A new differential code bias (C1–P1) estimation method and its performance evaluation

The current satellite clock products are computed using the ionosphere-free phase (L1/L2) and code (P1/P2) observations. Thus, if users conduct undifferenced positioning using these clock products together with C1 and P2 observations, the differential code bias (DCB) (C1–P1) should be properly compensated. The influence of DCB (C1–P1) on the undifferenced ambiguity solutions is investigated. Based on the investigation, we propose a new DCB (C1–P1) estimation method. Using it, the satellite DCB (C1–P1) can be computed. A 30-day (DOY 205–234, 2012) dual-frequency GPS data set is processed to estimate the DCB (C1–P1). Comparing the estimated results with that of IGS DCB products, the accuracy is better than 0.13 m. The performances of DCB (C1–P1) in the code-based single-point positioning, precise point positioning (PPP) convergence and wide-lane uncalibrated phase delay (UPD) estimation are investigated using the estimated DCB (C1–P1). The results of the code-based single-point positioning show that the influence of DCB (C1–P1) on the up direction is more evident than on the horizontal directions. The accuracy is improved by 50 % and reaches to decimeter level with DCB (C1–P1) application. The performance of DCB (C1–P1) in PPP shows that it can accelerate PPP convergence through improving the accuracy of the code observation. The computed UPD values show that influence of DCB (C1–P1) on UPD of each satellite is different, and some values are larger than 0.3 cycles.     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.     

THE GEODETIC LEVELLING OF CEYLON (1926–1929)

Abstract

The Net.—The total length of the lines of the level-net is roughly 2400 miles. The net comprises 27 circuits with perimeters varying between 74 and 268 miles, and is generally closer in the wet zone than in the sparsely populated and undeveloped dry zones. In 12 circuits there are differences of level exceeding 1000 feet. The highest point reached in the net is 6572 feet, and a branch line runs from Nuwara Eliya to the summit of Pidurutalagala, the highest mountain in the island (8282 feet).     

A new ΔLOD series in monthly intervals (1892.0–1997.0) and its comparison with other geophysical results

Using the ΔT (integrated variation of the Earth's rotation measured in terestrial time) series (1891.5–1955.5) derived from lunar occultation observations and the UT1–UTC (universal time–coordinated universal time) series (1955.5–1997.5) of the Bureau International de L'Heure/International Earth Rotation Service, a new ΔLOD (variation of the length of day) series in monthly intervals from 1892.0 to 1997.0 is calculated. Using digital filtering, the interannual and decadal components of the ΔLOD series are separated and then compared with those inferred from other geophysical quantities. It is shown that, on the interannual time scale, atmospheric processes can play an important role in exciting astronomical ΔLOD. However, the main oscillation with a mean period of about 5.8 years and peak-to-peak amplitude of about 0.3 ms in the residuals of ΔLOD(Astr) −ΔLOD(Wind) for 1968.0–1997.0 suggests that about half of the amplitude in astronomical ΔLOD must be excited by other geophysical processes, while on the decadal time scale the atmospheric excitation is too small. Geomagnetic core–mantle coupling may be a plausible source of the excitation of ΔLOD on the decadal time scale, but the geomagnetic data are still insufficient and an improved model of core–mantle coupling is required. Received: 3 April 1998 / Accepted: 31 May 1999     

Using Maximum Likelihood (ML) and Maximum A Prior Probability (MAP) in Iterative Self‐Organizing Data (ISODATA)

Abstract

With the availability of high‐resolution satellite imagery featuring as high as 1 meter resolution in the panchromatic mode and 3‐meter resolution in the multispectral mode, there is an interest by many new commercial and public service applications such as cellular telephones coverage area design, urban/land cover planning, and real estate marketing to extract features from images automatically. To that end, the demand for unsupervised classification techniques is growing. In this paper, the Maximum Likelihood (ML) and Maximum A prior Probability (MAP) algorithms are used as decision rules to find boundaries of classes computed by the Iterative Self‐Organizing Data (ISOADATA) algorithm. Different satellite images with different resolutions were used to experiment with these algorithms. The results of comparing and analyzing the algorithms revealed that MAP‐ISODATA performed better than ML‐ISODATA even when the same initial matrix was used. It was shown that there was no significant difference between ML‐ISODATA and MAP‐ISODATA in terms of accuracy. It was also realized that better results could be obtained if homogenous initialization strategies were used.     

Monitoring Urban Landscape Dynamics Over Delhi (India) Using Remote Sensing (1998–2011) Inputs

Urbanization is increasingly becoming a widespread phenomenon at all scales of development around the globe. Be it developing or developed nations, all are witnessing urbanization at very high pace. In order to study its impacts, various methodologies and techniques are being implemented to measure growth of urban extents over spatial and temporal domains. But urbanization being a very dynamic phenomenon has been facing ambiguities regarding methods to study its dynamism. This paper aims at quantifying urban expansion in Delhi, the capital city of India. The process has been studied using urban land cover pattern derived from Landsat TM/ETM satellite data for two decades (1998–2011). These maps show that built-up increased by 417 ha in first time period (1998–2003) and 6,633 ha during next period (2003–2011) of study. For quantification of metrics for urban expansion, the Urban Landscape Analysis Tool (ULAT) was employed. Land cover mapping was done with accuracy of 92.67 %, 93.3 % and 96 % respectively for years 1998, 2003 and 2011. Three major land covers classes mapped are; (i) built-up, (ii) water and (iii) other or non-built-up. The maps were then utilized to extract degree of urbanization based on spatial density of built-up area consisting of seven classes, (i) Urban built-up, (ii) Suburban built-up,(iii) Rural built-up, (iv) Urbanized open land, (v) Captured open land, (vi) Rural open land and (vii) Water. These classes were demarcated based on the urbanness of cells. Similarly urban footprint maps were generated. The two time maps were compared to qualitatively and quantitatively capture the dynamics of urban expansion in the city. Along with urbanized area and urban footprint maps, the new development areas during the study time periods were also identified. The new development areas consisted of three major categories of developments, (i) infill, (ii) extension and (iii) leapfrog.     

THE ART OF ORIGINAL CIRCULAR DIVIDING (1650–1850)

Abstract

The problem of dividing the circle into equal parts has occupied the minds of astronomers and instrument makers from the earliest times, but little is known of the methods adopted by such renowned observers as Hevelius or Tycho Brahe, who are said to have divided their own instruments (I). It is possible, however, to trace the various steps by which progress was made and to appreciate the urgent need that was felt, particularly throughout the eighteenth century, for improvement in the accuracy of astronomical instruments, if only to satisfy the increasing demands for navigational charts and for the means of determining the position of a ship at sea.     

CLAUDE REIGNIER CONDER (1848–1910) AND THE SURVEY OF PALESTINE

Abstract

Few surveyors can have been set a more interesting task than that which fell to the lot of Claude Conder, who first thoroughly explored and mapped the Holy Land some seventy years ago. His work is still of value, and must be referred to by all who are concerned with the ancient topography and archreology of that country. It may be found interesting to consider exactly what the task was, how it was accomplished, and something of the career of the young man who successfully carried it through.     

A global,high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

The science and management of terrestrial ecosystems require accurate, high-resolution mapping of surface water. We produced a global, 30-m-resolution inland surface water dataset with an automated algorithm using Landsat-based surface reflectance estimates, multispectral water and vegetation indices, terrain metrics, and prior coarse-resolution water masks. The dataset identified 3,650,723 km² of inland water globally – nearly three quarters of which was located in North America (40.65%) and Asia (32.77%), followed by Europe (9.64%), Africa (8.47%), South America (6.91%), and Oceania (1.57%). Boreal forests contained the largest portion of terrestrial surface water (25.03% of the global total), followed by the nominal ‘inland water’ biome (16.36%), tundra (15.67%), and temperate broadleaf and mixed forests (13.91%). Agreement with respect to the Moderate-resolution Imaging Spectroradiometer water mask and Landsat-based national land-cover datasets was very high, with commission errors <4% and omission errors <14% relative to each. Most of these were accounted for in the seasonality of water cover, snow and ice, and clouds – effects which were compounded by differences in image acquisition date relative to reference datasets. The Global Land Cover Facility (GLCF) inland surface water dataset is available for open access at the GLCF website (http://www.landcover.org).     

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

ABSTRACT

Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by consuming anywhere between 70% and 90% of all human water use globally. Given these facts and the increase in global population to nearly 10 billion by the year 2050, the need for routine, rapid, and automated cropland mapping year-after-year and/or season-after-season is of great importance. The overarching goal of this study was to generate standard and routine cropland products, year-after-year, over very large areas through the use of two novel methods: (a) quantitative spectral matching techniques (QSMTs) applied at continental level and (b) rule-based Automated Cropland Classification Algorithm (ACCA) with the ability to hind-cast, now-cast, and future-cast. Australia was chosen for the study given its extensive croplands, rich history of agriculture, and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing. This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m normalized difference vegetation index 16-day composite time-series data for 16 years: 2000 through 2015. The products consisted of: (1) cropland extent/areas versus cropland fallow areas, (2) irrigated versus rainfed croplands, and (3) cropping intensities: single, double, and continuous cropping. An accurate reference cropland product (RCP) for the year 2014 (RCP2014) produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015. A comparison between the ACCA-derived cropland products (ACPs) for the year 2014 (ACP2014) versus RCP2014 provided an overall agreement of 89.4% (kappa?=?0.814) with six classes: (a) producer’s accuracies varying between 72% and 90% and (b) user’s accuracies varying between 79% and 90%. ACPs for the individual years 2000–2013 and 2015 (ACP2000–ACP2013, ACP2015) showed very strong similarities with several other studies. The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015, thus highlighting the value of the study in food security analysis. The ACCA algorithm and the cropland products are released through http://croplands.org/app/map and http://geography.wr.usgs.gov/science/croplands/algorithms/australia_250m.html     

A Test of Central Place Theory Using Shuttle Imaging Radar (SIR‐A) of China's North Central Plain

Abstract

This study utilizes radar imagery to test the application of Walter Christaller's central‐place theory on China's North Central Plain. Examination of the spatial order and layout of settlements reveal that central place theory's transportation principle, k=4 exists. The study distinguishes four hierarchical settlement sizes and shows how effective rural societies are in evolving settlement structures whose spatial order and regularity avoids spatial inefficiencies. The advent of space based imaging systems such as SIR‐A radar imagery has permitted tests of new sites where the restrictive conditions of central place theory exist. These studies allow parallels to be drawn between the postulates of this theory of settlement structure and whether the theory is matched in reality.

This work is needed because of such scarcities. It allows the theory to undergo further subjections, a scrutiny needed for the validation, or otherwise of its postulates. The work adds to a large body of literature on this topic whose limitation has been the scarcity of actual test sites where theory and reality can be compared. The study presents positive indications that central place theory exists in reality, a compliment to the remarkable perceptions of Walter Christaller.