Synthesis of geophysical data with space-acquired imagery: A review

Geophysical data obtained from ground and airborne platforms have been used in the development of regional geologic models for many years. Space-acquired data and imagery have a shorter but similar history of applications. All these data may be synthesized either manually or digitally. Manual synthesis methods consist of overlaying and comparing maps, whereas digital synthesis methods consist of computer storage and analysis of registered digital data sets.A data base may include topographic, geologic, soils, aeromagnetic, gravity, radiometric, electromagnetic and geochemical data, and Landsat, Seasat, and Heat Capacity Mapping Mission (HCMM) images, all of which can be evaluated individually or compared in multiple layers (overlays).Stereographic models, useful in the correlation and interpretation of geophysical data, have been created from Landsat images by using aeromagnetic, gravity, geochemical, or topographic values to offset Landsat pixels, thus introducing parallax and permitting stereoscopic viewing.Statistical correlation has been used to determine the applicability of specific data sets to the development of geologic or exploration models. Various arithmetic functions have proven useful in developing models from such data sets.     

Spatio-temporal dynamics in the phenology of croplands across the Indo-Gangetic Plains

Spatio-temporal dynamics in land surface phenology parameters observed over croplands can inform on crop-climate interactions and, elucidate local to regional scale vulnerabilities either due to climate change or prevailing sub-optimal agricultural practices. Here, we observe spatio-temporal trends in land surface phenology parameters (cropping intensity, length of growing season and productivity) for kharif and rabi cropping seasons from satellite data across the Indo-Gangetic Plains from 1982 to 2006. The productivity of the Indo-Gangetic Plains croplands is of regional importance and is a vital component of Indian national food security efforts. Aside from local and intra-state heterogeneity in observed trends there was a clear west-to-east gradient in cropping intensity. Key observed trends include increasing cropping intensity in the eastern IGP, increasing number of growing days per year in Bihar, Uttar Pradesh and Haryana and increasing productivity in both cropping seasons across the IGP. This information is a crucial input to integrated assessments of the croplands to ensure management of the agricultural system shifts towards a trajectory of climate-resilience and environmental sustainability.     

Enhanced Landsat and HCMM imagery for mineral exploration in contrasting areas of subtropical humid and semi-arid terrain

The role of multispectral and thermal imagery in mineral exploration is evaluated for two areas with favourable geological conditions within contrasting physical environments — one in the semi-arid low tree and shrub savannas of western Queensland and northern South Australia, the other in the humid subtropical forest zone of western Yunnan, China.For both areas Landsat imagery was used to identify structures and lithologies favourable for mineralization and locate ironstones/gossans indicative of mineralized bedrock. HCMM imagery was used alongside Landsat imagery to identify former and ephemeral drainage patterns important for the interpretation of geochemical data over covered ground in Australia. Interpretations were made of enhanced colour composites, outputs of MSS band ratios and colour rotated images generated from both NASA film products and CCTs. These were checked by field studies during which plant, soil and rock chip samples for subsequent metals analyses were collected from areas of anomalous vegetation and from barren ironstones. Some rock chip samples from Australia contained concentrations of copper or lead or small amounts of other metals. In China geobotanical anomalies over ironstones from which soil and rock samples yielded copper, lead, zinc, tin and silver suggest the presence of a major belt of potential multi-metal mineralization.     

Mapping recent agricultural developments in China from satellite data

Landsat data have been employed to study and map agricultural developments in three regions of China: 1) Pearl River delta; 2) Nen River basin; and 3) Xinjiang Autonomous Region. Manual interpretation procedures used in conjunction with multi-date Landsat images and collateral information permitted rice yields to be estimated for the Pearl River delta in 1978. A combination of manual and computer-assisted analyses of Landsat data of Northeast China revealed that more than 15,000 km² of agricultural land in a 184,500 km² study area had been reclaimed from rangeland and marshland. These analyses also indicated a shift in cropping practices, with the foodcrops wheat and corn replacing cash crops such as soybeans. In the arid west, Landsat image data provided valuable input to a geographic information system (GIS). It appears the GIS approach will prove useful for evaluating agricultural land potential in the remote areas of China.     

Inferring non-point pollution from land cover analysis

Best Management Practices (BMP's) in farming were found to significantly reduce agricultural non-point water pollution in Central Indiana. Through the implementation of systems of conservation tillage practices and structural measures at the farm level, reductions in runoff were achieved, thereby minimizing erosion and subsequent sedimentation and pollution of the surface water system.These conclusions resulted from a three and one-half year study entitled, “The Indiana Heartland Model Implementation Project” administered by the Indiana Heartland Coordinating Commission, involving cooperation and coordination of farmers, citizens, and a multi-agency, multi-disciplinary team comprised of four universities and numerous governmental agencies. The U.S. Environmental Protection Agency funded research, while the U.S. Department of Agriculture provided cost share monies for BMP implementation.A comprehensive geographically encoded computer-aided data base was constructed which included information on land cover, elevation, slope, aspect, soils, etc. Land cover map files were compiled through remote sensing including Landsat MSS digital data and low altitude color infrared aerial photography sources. This digital data base was suited for spatial and statistical analyses and transferred easily as input to Purdue University's ANSWERS Model for further watershed assessment. The ANSWERS Model is a distributed deterministic model which simulates the monitored reaction of subwatersheds to actual storm events. Through this model inferences were made as to the expected water quality improvements, given BMP's were implemented at critical areas for erosion throughout both watersheds.     

Mixed surface reflection functions determined from a priori knowledge and satellite radiance

A method to derive mesoscale area means of surface solar flux densities from a priori knowledge and actual cloudfree satellite radiances is presented. It is based on the concept of the mixed reflection function which can be derived from existing data. Herewith and with actual atmospheric data derived from the operational meteorological network the cloudfree radiation field is computed. By comparison of computed and measured satellite radiance the surface albedo of the model is tuned. In a case study this method is applied to an agricultural region called La Mancha, Spain, and comprehensively checked against airborne radiance measurements. The surface albedo can be determined to about ± 0.01.     

Farming in space: environmental and biophysical concerns.

The colonization of space will depend on our ability to routinely provide for the metabolic needs (oxygen, water, and food) of a crew with minimal re-supply from Earth. On Earth, these functions are facilitated by the cultivation of plant crops, thus it is important to develop plant-based food production systems to sustain the presence of mankind in space. Farming practices on earth have evolved for thousands of years to meet both the demands of an ever-increasing population and the availability of scarce resources, and now these practices must adapt to accommodate the effects of global warming. Similar challenges are expected when earth-based agricultural practices are adapted for space-based agriculture. A key variable in space is gravity; planets (e.g. Mars, 1/3 g) and moons (e.g. Earth's moon, 1/6 g) differ from spacecraft orbiting the Earth (e.g. Space stations) or orbital transfer vehicles that are subject to microgravity. The movement of heat, water vapor, CO2 and O2 between plant surfaces and their environment is also affected by gravity. In microgravity, these processes may also be affected by reduced mass transport and thicker boundary layers around plant organs caused by the absence of buoyancy dependent convective transport. Future space farmers will have to adapt their practices to accommodate microgravity, high and low extremes in ambient temperatures, reduced atmospheric pressures, atmospheres containing high volatile organic carbon contents, and elevated to super-elevated CO2 concentrations. Farming in space must also be carried out within power-, volume-, and mass-limited life support systems and must share resources with manned crews. Improved lighting and sensor technologies will have to be developed and tested for use in space. These developments should also help make crop production in terrestrial controlled environments (plant growth chambers and greenhouses) more efficient and, therefore, make these alternative agricultural systems more economically feasible food production systems.     

Estimating irrigation water use and withdrawal of ground water on the High Plains,U.S.A.

In four decades following the Dust Bowl days of the 1930's, extensive areas of dry farming and rangeland on the semi-arid U.S. High Plains were transformed into a vast region of irrigated oases, producing meat and grain for much of the world. The agricultural economy has experienced such rapid growth in part because of the availability of ground water and because of development of new irrigation technology to use that water for agriculture. However, more water is being used than is being replaced. To estimate both the volume of water withdrawn and the regional scope of the problem a technique has been developed that combines multispectral data from Earth-orbiting satellite with known pumpage data for the same growing season. The location and extent of irrigated cropland—some with different crops watered at different times—is inventoried using computer-assisted analysis of the data from Landsat. The amount of water used is estimated by multiplying and summing surface area of irrigated agriculture and the average measured pumpage from sampled sites. Published findings to date are cited in the Selected References. All suggest transferability of a promising technology to the study of land transformation processes elsewhere.     

地基行星大气掩星观测资料流程和数据整理

在中国火星探测萤火一号(YH-1)计划中, 包括了地基掩星观测反演火星大气的科研任务. 观测资料整理是反演流程的第一步. 本文描述了地基火星大气掩星观测处理软件系统的观测数据流程和观测资料整理模块,并详细介绍了观测资料整理模块的结构和功能, 其中包括时间系统转换、历表插值、坐标系变换、信号时延改正以及掩星平面建立. 利用行星数据系统公布的火星快车无线电科学数据和由SPICE得到的地球、火星历表以及火星快车的轨道数据, 结合本文的算法, 得到了一些实验结果.      

Identification and dynamics of agricultural environments in Northeast Thailand from landsat images (1972, 1976, 1982)

The objective of this research is to prepare a cartographic methodology to present agricultural environments and their dynamics from satellite data. Three Landsat images (October 1972, January 1976, January 1982) have been used and a field survey has been done in 1984. After interactive processing on TRIAS system of Institut Geographique National (IGN). Five colour maps have been produced:

• - a spatio-map with the new roads (1:250,000);
• - a map of the surface-states in 1982 (classified image) using a comparison with the two other dates for improvement (1:250,000);
• - a map of agro-ecological landscape units based on the combination between surface states showing interrelationships between agrarian systems and bio-physical environment (1:5000,000);
• - a map of the surface moisture seasonal variations to show the availability of water for the agriculture (1:400,000);
• - a map of changes in some agricultural environments components (1972–1982): water and flooded areas, agricultural areas, forests (1:500,000).

     

Evaluation of thematic mapper data for mapping forest,agricultural and soil resources

Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.     

Remote sensing techniques for monitoring and managing irrigated lands

Agriculture in semi-arid tracts of the world depends on water to sustain its irrigation systems. Such agricultural systems either derive from government investments in the control of surface flow or they have been developed through the exploitation of groundwater sometimes by a large community of unsupervised individuals seeking to maximise their own advantage without concern for the resource upon which they depend in the medium and long term. In both cases government agencies need data on the area irrigated and the volume of water used. In countries with highly developed scientific and agricultural institutions the contribution of remote sensing, though significant, may only provide between five and ten per cent of the data required to guide regional and national managers. In countries without such institutions the proportion contributed by remote sensing can be very much higher, as shown in a recent study in North Africa. The paper will emphasise the importance of carefully structured sampling procedures, both to improve the areal estimates from satellite imagery and the estimates of water use based upon them. The role of satellite imagery in providing information on the status of water resources, on trends in water use and in the implementation of policies to extend or diminish irrigated land are discussed.     

Effects of concurrent snow and cloud cover on planetary albedo

The effects of snow and cloud cover on planetary albedo are examined using observations from NOAA polar orbiting satellites. Reflected radiation was measured in the visible range (0.5 – 0.7 μm). Planetary albedos resulting from different cloud/snow cover conditions are compared using Northern Hemisphere snow cover maps, surface weather charts, satellite photos and data on land surface types. None of the cases studied show that concurrent cloud and snow cover produces significantly different planetary albedos than cloud cover alone. Cloud cover alone is found to yield higher planetary albedos than snow cover alone; the difference being greatest over forested areas. With and without snow cover present, clear-sky planetary albedos over farming and grazing lands (snow(0.45), no snow(0.15)) are found to be significantly higher than those over forested regions (snow(0.33), no snow(0.11)). Variations in satellite zenith angle are not found to produce significant effects in most cases studied.     

A study of backscattered spectra dynamics of agricultural crops during growth period on the territory of the Krasnoyarskii Krai (Russia)

The work presents the results of the study aimed at determining the seasonal dynamics of the spectral brightness and reflectance of agricultural crops (wheat, barley and oats) in the Krasnoyarskii Krai (Russia). The analysis of spectral curves obtained through field ground measurements and from satellite data showed that fine spectral differences can be used to study the spatial distribution of various types of vegetation and their ecological state. Based on the created electronic spectral brightness data base, the possibilities are shown of using spectrophotometric information for determining morphophysiological changes occurring in the plants and their species composition. The determined contrasts can be effectively used to obtain necessary information while processing space images, which suffer from natural interferences (varying optical thickness of the atmosphere, cloudiness, alterations in the scanner’s angle of view, varying solar height, and highly inhomogeneous underlying surface).     

Impact of emissions from anthropogenic sources on satellite-derived reflectance

The present study deals with the impact of extensive anthropogenic activities associated with festivities and agricultural crop residues burning in the Indo-Gangetic Plains (IGP) on satellite-derived reflectance during November 2007. Intense smoke plumes were observed in the IRS-P4 OCM satellite data over IGP associated with agricultural crop residue burning during the study period. Terra-MODIS AOD and CALIPSO LIDAR backscatter datasets were analysed over the region to understand the spatial and temporal variation of the aerosol properties. Ground-based measurements on aerosol optical properties and black carbon (BC) mass concentration were carried out during 7–14 November 2007 over urban region of Hyderabad, India. Top of the Atmosphere (TOA) reflectance estimated from IRS-P4 Ocean Color Monitor (OCM) data showed large variations due to anthropogenic activities associated with crop residue burning and fireworks. Atmospheric corrections to OCM satellite data using 6S radiative transfer code with inputs from ground and satellite measurements could account for the variations due to differential aerosol loading. Results are discussed in this paper.     

Classification of multitemporal Sentinel-2 data for field-level monitoring of rice cropping practices in Taiwan

Cadastral information of rice fields is important for monitoring cropping practices in Taiwan due to official initiatives. Remote sensing based rice monitoring has been a challenge for years because the size of rice fields is small, and crop mapping requires information of crop phenology, relating to spatiotemporal resolution of satellite data. This study aims to develop an approach for mapping rice-growing areas at field level using multi-temporal Sentinel-2 data in Taiwan. The data were processed for 2018, following four main steps: (1) construct time-series Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), (2) noise filtering of the time-series data using wavelet transform, (3) rice crop classification using information of crop phenology, and (4) parcel-based accuracy assessment of the mapping results. The parcel-to-parcel comparisons between mapping results and ground reference data indicated satisfactory results. These findings were confirmed by close agreement between satellite-derived rice area and government’s statistics. Although some factors, including mixed-pixel issues and cloud-cover effects, lowered the mapping accuracies of townships along the coastline, this study has demonstrated the efficacy of using multitemporal Sentinel-2 data to create a reliable database of rice-growing areas over a large and heterogeneous region. Such a quantitative information was important for updating rice crop maps and monitoring cropping practices.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

Selection of classification techniques for land use/land cover change investigation

The concerns over land use/land cover (LULC) change have emerged on the global stage due to the realisation that changes occurring on the land surface also influence climate, ecosystem and its services. As a result, the importance of accurate mapping of LULC and its changes over time is on the increase. Landsat satellite is a major data source for regional to global LULC analysis. The main objective of this study focuses on the comparison of three classification tools for Landsat images, which are maximum likelihood classification (MLC), support vector machine and artificial neural network (ANN), in order to select the best method among them. The classifiers algorithms are well optimized for the gamma, penalty, degree of polynomial in case of SVM, while for ANN minimum output activation threshold and RMSE are taken into account. The overall analysis shows that the ANN is superior to the kernel based SVM (linear, radial based, sigmoid and polynomial) and MLC. The best tool (ANN) is then applied on detecting the LULC change over part of Walnut Creek, Iowa. The change analysis of the multi temporal images indicates an increase in urban areas and a major shift in the agricultural practices.     

Survey of CELSS concepts and preliminary research in Japan

Many agricultural and other experiments relating to the development of a Controlled Ecological Life Support System (CELSS) were proposed by scientists throughout Japan in the fall of 1982. To develop concrete experimental concepts from these proposals, the engineering feasibility of each proposal was investigated by a CELLS experiment concept study group under the support of the National Aerospace Laboratory. The conclusions of the group were described in two documents, /1/, /2/. Originally, the study group did not clearly define necessary missions leading to the goal of an operational CELSS for spaceflight. Therefore, the CELSS experiment concept study group met again to clarify the goals of CELSS and to determine three phases to achieve the goals. The resulting phases, or missions, and preliminary proposals and studies needed to develop a CELLS are described herein.     

An Integer Precise Point Positioning technique for sea surface observations using a GPS buoy

GPS data dedicated to sea surface observation are usually processed using differential techniques. Unfortunately, the precision of resulting kinematic positions is baseline-length dependent. So, high precision sea surface observations using differential GPS techniques are limited to coasts, lakes, and rivers. Recent improvements in GPS satellite products (orbits, clocks, and phase biases) make phase ambiguity fixing at the zero difference level achievable and opens up the observation of the sea surface without geographical constraints. This paper recalls the concept of the Integer Precise Point Positioning technique and discusses the precision of GPS buoy positioning. A sequential version of the GINS software has been implemented to achieve single epoch GPS positioning. We used 1 Hz data from a two week GPS campaign conducted in the Kerguelen Islands. A GPS buoy has been moored close to a radar gauge and 90 m away from a permanent GPS station. This infrastructure offers the opportunity to compare both kinematic Integer Precise Point Positioning and classical differential GPS positioning techniques to in situ radar gauge data. We found that Precise Point Positioning results are not significantly biased with respect to radar gauge data and that horizontal time series are consistent with differential processing at the sub-centimetre precision level. Nevertheless, standard deviations of height time series with respect to radar gauge data are typically [4–5] cm. The dominant driver for noise at this level is attributed to errors in tropospheric estimates which propagate into position solutions.