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Tingginya tingkat urbanisasi menyebabkan meluasnya wilayah perkotaan dan menciptakan daerah keras yang mengakibatkan suhu tinggi di wilayah perkotaan, termasuk Banda Aceh. Permasalahan ini tentu menimbulkan ketidaknyamanan bagi masyarakat Banda Aceh. Beberapa penelitian melaporkan bahwa suhu udara yang terlalu tinggi dapat menyebabkan masalah kesehatan yang serius di masyarakat. Suhu permukaan Banda Aceh diukur menggunakan Spectral Radiance dari Satellite Imager, kemudian dibandingkan dengan data yang diukur langsung di lokasi penelitian. Hasil menunjukkan suhu udara di Banda Aceh berkisar antara 22,32°C hingga 34,86°C. Selain itu, terjadi korelasi antara penggunaan ruang dengan tingkat suhu udara Banda Aceh berdasarkan parameter hard area dan vegetasi. Namun, hanya variabel jarak dengan badan air yang memiliki korelasi signifikan terhadap perubahan tingkat suhu. Surface Temperature Distribution Using Spectral Radiance from Satellite Imagery: A Case Study in Banda Aceh Abstract . The high rate of urbanization will have an effect on land change. The increasing number of buildings and lack of green open space will hinder the direction of wind speed, cause inconvenience to the public. The purpose of this study was to determine the distribution of surface temperature in the city of Banda Aceh based on the spectral emission of Landsat images from vegetation density, distance from the river, and built-up area. The air temperature data were obtained using the classification method from the digital number value of the Landsat image to the spectral radiance and then converted into air temperature. The density of the built-up area was analyzed from the Normalized Difference Vegetation Index (NDBI) and the density of the vegetation was analyzed from the Normalized Difference Vegetation Index (NDVI). The air temperature distribution map from the image is divided into 3 zones that are densely populated (built-up area), vegetation and distance to water bodies to be measured directly in the field. The air temperature from the lansat 8 images ranged from 22.32°C to 34.86°C. The zone with a distance of 3,457 km from a water body, with less vegetation density (

Green bands in satellite remote sensing play an important role in monitoring water and vegetation information. Due to the lack of observed green band, the Geostationary Operational Environmental Satellite (GOES-16) Advanced Baseline Imager (ABI) sensor uses a synthetic one. This study presents an ABI green band generation method using the Pix2Pix based on conditional generative adversarial networks (CGANs) and convolutional neural network techniques with data observed in the visible range of the GOES-16/ABI sensor. Our model was constructed from the radiance data sets in the red, blue, and green bands of the Advanced Himawari Imager (AHI) onboard Himawari-8/9 satellites from August 27, 2018 to May 1, 2019, and applied to generate a GOES-16 ABI green band using the ABI blue band radiance data. A comparison between the AHI and the Pix2Pix-generated AHI green bands displayed high accuracy, evaluated through bias = 0.120, root mean square error (RMSE) = 0.983 in digital number (DN) units, and correlation coefficient (CC) = 0.999. Furthermore, comparison between the Pix2Pix-generated and synthetic ABI green bands resulted in a good agreement (bias = 1.029 and RMSE = 2.892 in DN units, CC = 0.993). The statistical comparison between the green band, and red or blue band resulted in the exceptional performance of the Pix2Pix-generated ABI green band compared to the synthetic ABI green band. Consequently, our Pix2Pix-based model can be effectively used to generate nonexistent green band of ABI sensor and be applied in a variety of scientific applications requiring green band.

River Beas originates in the Himalayas in Central Himachal Pradesh, and merges with river Sutlej at Harike in the state of Punjab and this river is a habitat of the endangered freshwater dolphin, Platanista gangetica minor R. The pollution of water bodies is a significant environmental jeopardy as the river is the prime source of water for the consumption by human beings and aquatic species residing in the river. The water quality indices (WQI) of the river Beas using nine standard parameters recommended by National Sanitation Foundation, were determined for pre-monsoon, post-monsoon and winter seasons at three sampling sites between the towns of Beas and Harike over a stretch of 63 km. The results of WQI of river Beas at Harike before confluence with river Sutlej and at Goindwal Sahib is superior to those at the Beas bridge. This is due to self-purification of the water downstream from Beas bridge to Harike. Season-wise, water quality during the pre-monsoon season was somewhat superior at Harike and Beas. This is attributed to fast degradation of organic matter in river during the summer season. Bioassay for appraising the toxicity of river water was also determined by using Girardinus guppii fish and their results indicate that the water of river Beas is not toxic. Toxicity bioassay using Girardinus guppii fish indicates that the water of river Beas is not toxic. Digital number (DN) values of the river water were obtained from Landsat-TM imagery. $${\text{PO}}_{4}^{{3 - }}$$ , TDS and turbidity of the river water were regressed on the reflectance values. Using multiple and β-regression analysis, it was found that $${\text{PO}}_{4}^{{3 - }}$$ , TDS and turbidity contribute positively to band 2(G) and negatively to band 3(R). Multiple linear regression and β-regression analysis showed that $${\text{PO}}_{4}^{{3 - }}$$ and turbidity are regressed on the normalized difference water index negatively and positively respectively. Correlations between the target and output values from artificial neural network for $${\text{PO}}_{4}^{{3 - }}$$ , TDS and turbidity were highly significant. It is suggested that removal strategies like introduction of aquatic phytoremediation plants must be involved in land management policies in order to mitigate the anthropogenic jeopardy. We affirm that the significance of applying water quality management tools using nature dependent solutions and well-organized management policies.

With the speedy development of the economy and the advancement of urbanization, the number of communication mediums and transportation is increasing instantaneously that's why Bangladesh needs a smart solution in every sector. In this paper, RFID and Image processing based automated toll collection system is introduced to monitor the toll plaza. A road zipper device is introduced for a proper lane management system that helps to reduce the traffic jam. Two step-based toll collection system ensured the specification of the vehicle then deduct the toll amount from their account without stopping the vehicles. For this proposed model, vehicles need to insert a digital number plate and the number plate information is embedded on the RFID tags. This paper presents a prototype of a road zipper and automatic toll collection device that gives proper results as expected. This system is automated, so it reduced human error. Thus, making an intelligent transportation system will become easier.

Gaofen 2 (GF-2) high spatial resolution imagery has been recognized as an important data source for mapping vegetation pattern dynamics. The Kauth-Thomas (KT) indices of brightness, greenness, and wetness derived from single-date imagery has also been proved to be better than the common vegetation indices in monitoring the vegetation, mapping land desertification, and classifying land covers. However, for change detection of vegetation status, multitemporal Kauth-Thomas (MKT) transformation is found to be a more effective approach. In this paper, the parameters defining the KT dimensions for single-date mIHS pansharpeniing GF-2 data (acquired on April 30, 2016) were derived. Then, the MKT transformation matrix was proposed using a linear transformation process, which could be applied to GF-2 digital number image data for detecting vegetation pattern dynamics in the future.

Mangrove resources provide economic and ecological value. The expansion of residential areas makes the level of need for shelter as well as the region increases. This will have an impact on the utilization of mangrove in sufficient needs such as firewood, charcoal and building materials. If continue berlasngsung then do not deny the existence of mangrove degradation. The occurrence of mangrove degradation will have a direct impact on the local community. Considering the importance of mangrove function and the need for data of mangrove area change, it is needed to analyze the change of mangrove area in coastal of Bangka Tengah, which will be analyzed within 15 years in 2002 and 2017, so that the result of this study is expected to be further management by local government to conserve mangrove forests. This research was conducted from December 2017 to March 2018 with location station determination based on unsupervised image classification, that is classification based on digital number using RGB_231 image composite for ASTER image. Based on the results of the study, there is a change of mangrove area from 2002-2014 as much as 176.3 Ha or about 15.95% and in 2014-2017 there is an increase of 36.23 Ha or about 3.9%. The value of NDVI analys in East Coast of Central Bangka Regency in 2017 ranges from 0.005 to 0.156. the occurrence of the reduction of mangrove area due to the changing function of mangrove land into settlement, mangrove logging in the utilization of charcoal and mining industry. The addition of the extent of the addition of seedlings along the coast of Kurau and Penyak.

REMOTE SENSING FOR COASTAL STUDIES. Coastal ecosystem is an ecological system that is important and the most productive area on earth. On the other hand, pressure on coastal ecosystems for human necessity cause decrease quality of coastal ecosystems. Utilization of coastal areas requires the proper management and suitable with objective. Good management requires appropriate information for decisionmaking. For spatial data, acquisition of information through remote sensing data is the best option. This paper will discuss the utilization of using remote sensing for coastal analysis. Coastal management requires information accurately and quickly to follow up issues or problems that growth up. Remote sensing has provided the capability to provide that information by translating information from digital number to thematic information. Regardless from the problem existing mapping method, utilization remote sensing in the future will be the main data on coastal management, especially in the monitoring and measurement of biophysical parameter in coastal areas.

In this paper, a most significant bits (MSBs) prediction strategy for the design of successive approximation register (SAR) analog-to-digital converter (ADC) in battery pack voltage detection is proposed to reduce conversion time without losing accuracy. The strategy takes advantage of the battery pack voltages characteristics where there is a strong correlation among neighboring cell voltage values. By generating the MSBs with the quantization results of the battery pack in the previous loop, the ADC just needs to convert the remaining least significant bits (LSBs). This paper analyzes the relationship between saved time and five parameters: reading frequency (f), cell number of battery pack (N), cell number (CN) for MSB-prediction, standard deviation (σ), change rate of digital number (K), which can give a feasible prediction on saved working time in any conditions. With this strategy, in a f = 50 kHz, N = 10, CN = 8, σ = 10 system, up to 27.83% A/D conversion time can be saved in charging state, and 27.89% A/D conversion time can be saved in discharging state.

When assessing remote sensing data, nighttime light data have shortcomings that can be attributed to sensor limitations and the influence of the natural environment. Signal leakage errors in nighttime light data were identified in this study. A regression model was created to reduce signal leakage error by selecting sampling points in coastal area. Lighting variations in Edogawa between 2008 and 2013 were compared based on the Defense Meteorological Satellite Program’s nighttime light data. The lighting variation characteristics in Edogawa from 1992 to 2012 at 5-year intervals were also analyzed. The results show that the 2002 FIFA World Cup held in Japan led Edogawa’s light digital number values to peak in 2002. The annual Edogawa lighting changes from 2007 to 2013 were also explored. The 2008 global financial crisis led to the lowest compounded night light index and average digital number in Edogawa during these 7 years.

This article proposes a simple statistical approach to combine nighttime light data with official national income growth figures. The suggested procedure arises from a signal-plus-noise model for official growth along with a constant elasticity relation between observed night lights and income. The methodology implemented in this paper differs from the approach based on panel data for several countries at once that uses World Bank ratings of income data quality for the countries under study to produce an estimate of true economic growth. The new approach: (a) leads to a relatively simple and robust statistical method based only on time series data pertaining to the country under study and (b) does not require the use of quality ratings of official income statistics. For illustrative purposes, some empirical applications are made for Mexico, China and Chile. The results show that during the period of study there was underestimation of economic growth for both Mexico and Chile, while official figures of China over-estimated true economic growth.

Though coastal blue spectrum is used in many domain of earth remote sensing, a majority of multispectral missions are still ignored it. This paper proposed a coastal blue reconstructing method by common-used blue spectrum with ZY-1(02D) data. The reconstructing method was established by three mathematical models: 1) the relation model of surface reflectance based on the responsivities for terrestrial objects; 2) the relation model of apparent radiances based on the radiance transferring model for earth-observing; 3) the relation model of image gray scale based on the imaging theory of multispectral cameras. Comparisons of image digital number and surface reflectance between the reconstructed coastal blue data and raw coastal blue data showed the relative errors of 4.87% with image gray scale and 3.15% with surface reflectance. The results demonstrate the feasibility of reconstructing and expanding spectrum for major multispectral missions without coastal blue.

The study devoted to problem of landslide dynamic in the territory of Dnipropetrovsk oblast. Study area covered right bank of Dnipro river, between Dnipro and Kamyanske cities. The territory characterized with hilly plain relief on loss soils. Specific combination of geomorphological and climate factors within the territory causes appearance the huge number of landslides. According to the highlighted problems the main aim of this study was to check the hypothesis about long-term dynamic and relation between activation of landslide processes and sunspot activity. The secondary aim was to determine stable diagnostic signs of landslides using satellite images. In accordance to aims the data base of Landsat images was created. The time series of images covered warm season during twenty years period (from 1988 till 2011 years). At the first stage of the study images were preprocessed and digital number was converted into reflectance values. Its allowed to investigate changes of surface type in long term dynamic. The surface changes were studied within locations of active and non-active landslides. There are all over 90 known locations where landslides took placed within this territory. The spectral analysis determined that most relevant signs of landslide are changes with vegetation and soil cover. According to this, the dynamic of surface type transformations was studied using normalized built-up and vegetation indexes (NDBI and NDVI). However, in the urban territory there were problems with recognition type of surface because of insufficient space resolution of Landsat images. This issue had medium influence on the statistical reliability of correlation value. Nevertheless, correlation and in-row statistical analysis showed cyclic and trend type of surface dynamic. More than half of locations characterized with cyclic dynamic, and the last part – with trend dynamic. The zero hypothesis about statistical homogeneity of extremum values NDVI and NDBI confirmed at significance level 0,5. General long-term tendency of NDBI and NDVI has opposite character to itch other: NDBI trend is descending, NDVI – is rising. It allowed to conclude about stabilization of landslides processes in the territory. However, the central hypothesis of the research was confirmed partially. The main part of landslide events took placed in the beginning and in the end of summer seasons of 1988, 2001 and 2007 years. The first pair of years matched with the highest sunspot activity.

With the continued development and economic growth, Bangladesh needs to be digitalized in every way possible. In this paper, RFID based Automated Toll Collection System is introduced as a solution of the traffic problems and also to maintain transparency in the toll collection system. The proposed system aims to make a digital toll collection system which can eliminate the delay on toll roads, toll bridges and toll tunnel without cash and without requiring cars to stop. This paper focuses on an electronic toll collection system which uses radio frequency identification (RFID) technology to identify a vehicle specifically for collecting toll. The proposed RFID system uses tags that are mounted on the digital number plate of the vehicles, through which information embedded on the tags are read by RFID readers. It is possible to reduce the need for vehicle owners and toll collection authorities to distribute tickets and collect tolls manually in this system Information on the toll payment can also be easily exchanged between the vehicle owners and toll authorities. As a result, transparency in toll payment can be ensured with reduced manual labor and human errors. Thus, building smart transportation system will become easier.

This study examined variability in the quantity and type of math talk used by caregivers and their children during traditional and digital number board game play, and further examined how brief guidance might increase math talk in both game conditions. Sixty-three caregiver-child (3-to-5-years old; M = 53.32 months) dyads played a traditional board game (Chutes and Ladders) and a digital version of the same game. Half of the participants received a verbal prompt to encourage caregivers to foster their children's math skills during game play. Results showed that caregivers' and their children's talk about math was significantly higher in the traditional game condition. Caregivers and their children also engaged in significantly more math talk related to counting and identifying numerals in traditional board game play. Use of a prompt did not promote caregivers' math talk in either of the game conditions.

The Defense Meteorological Satellite Program/Operational Linescane System (DMSP/OLS) stable night-time light (NTL) data showed great potential in urban extent mapping across a variety of scales with historical records dating back to 1990s. In order to advance this data, a systematic methodology review on NTL-based urban extent mapping was carried out, with emphases on four aspects including the saturation of luminosity, the blooming effect, the intercalibration of time series, and their temporal pattern adjustment. We think ancillary features (e.g. land surface conditions and socioeconomic activities) can help reveal more spatial details in urban core regions with high digital number (DN) values. In addition, dynamic optimal thresholds are needed to address issues of different exaggeration of NTL data in the large scale urban mapping. Then, we reviewed three key aspects (reference region, reference satellite/year, and calibration model) in the current intercalibration framework of NTL time series,...

In the Great East Japan Earthquake that occurred on March 11, 2011, the Pacific Ocean coast of the Tohoku region suffered serious tsunami damage. To draw up reconstruction plans following great earthquakes in such areas it is necessary to estimate the amount of disaster waste. Disaster waste estimation using remote sensing data is a fundamental priority that affects all subsequent processing. Although high ground resolution remote sensing data contain detailed information, they represent a narrow scanning width and are expensive. On the other hand, remote sensing data of lower ground resolution (5 to 30 m) are able to cover wide areas at a low cost. However, the digital number (DN) of each lower resolution pixel represents the average land cover conditions, i.e., the information provided by a pixel should be represented as a one-pixel mixed class (“mixel”) instead of one-pixel one-class. In a previous study, we developed a method for unmixing mixels using the DNs from RapidEye data. We also developed a method of disaster building domain estimation using RapidEye data acquired before and after an earthquake. In this study, we propose a method to estimate the number of disaster buildings using the results of the disaster building domain, whose effectiveness was confirmed by our findings.

Air pollutant of PM10 concentration over Bandung City was estimated based on satellite imagery. The imagery was acquired by Landsat -8 on 22nd May 2019. The methodology implementation were started with pre-processing includes geometric correction, radiometric calibration to converted of digital number into surface reflectance values to estimated PM10 concentration. For calculated the algorithm of PM10 need the coeficient aerosol optical depth (AOD) was using from AERONET. The results showed that the estimation of PM10 distribution through satellite imagery in Bandung in the year of 2019 in average 36.18 μg/m3. According to Air Pollution Standard Index from that average Bandung city is still in healthy category of PM10 concentration. The calculated data on PM10 were also compared with ground measurements of PM10 data estimated from different locations of Bandung for validation and a linear relationship was established between them having a moderate positive relationship with the correlation coefficient value of 0.6187.

Monitoring the growth of rice in Indonesia is very important because rice is a staple food of the Indonesian people. The biggest rice producer in West Java is Indramayu. Soil moisture is one of factor in monitoring the growth of paddy. The Monitoring is carried out using SAR image, namely Radarsat-2 Quad-Polarimetric imagery. In estimating the value of soil moisture, required a dielectric constant which is obtained from the value of the Digital Number (DN) that is converted into the backscattering value (σo). The approach that used in calculating the dielectric constant is a semi-empirical approach using the Dubois model (1995). The purpose of this study is to estimate the value of soil moisture in order that it can be used in monitoring the growth phase of paddy. The rice growth phase is distinguished in the form of a graph subsequently matched with the results of field photo validation. The results of this research show a positive linear correlation between the Dubois model (1995) and field soil moisture with a level of accuracy of ± 7.202% volumetric.

Background Hemispherical photography (HP) is a popular method to estimate canopy structure and understorey light environment, which analyses photographs acquired with wide view-angle lens (i.e. fisheye lens). To increase HP accuracy, the approaches of most previous studies were to increase the preciseness of exposure and thresholding of photographs, while ours quantified effects of canopy properties (gap fraction and length of sky-canopy border (SCB)) and errors of exposure and thresholding on the accuracy of HP. Results Through analysing photographs of real and model canopies, it was showed that HP inaccuracy resulted from the mismatch between exposure and thresholding rather than exposure or thresholding errors alone. HP inaccuracy was a function of the SCB length and the extent of exposure and thresholding errors, but independent of gap fraction. Discussion In photographs, SCBs are recorded as grey pixels which greyness is in between that of sky and canopy pixels. When there are exposure and thresholding errors, grey pixels are those prone to be misclassified in image analysis. Longer (vegetation with taller canopies) and wider (lower image sharpness) SCBs in photographs can both result in a higher amount of grey pixels and ultimately higher HP inaccuracy for a given extent of exposure and threshold errors. Conclusions Using lenses with view angle narrower rather than that of fisheye lens can shorten the SCB length in photographs and in turn reduce HP estimation inaccuracy for canopy structure and understorey light environment. Since short SCBs and low levels of exposure and thresholding errors can both result in low HP inaccuracy, to identify the true performance of new exposure and thresholding methods for HP, photographs recording canopies with long SCBs and acquired with fisheye lenses should be used. Because HP inaccuracy in a function of the amount of grey pixels resulting from SCBs, the amount of these pixels in photographs can be used as a universal parameter to quantify canopy properties influential to HP estimation and in turn make cross-study comparisons feasible. Electronic supplementary material The online version of this article (10.1186/s40529-018-0235-9) contains supplementary material, which is available to authorized users.

Brightness of nighttime lights has been used as an indicator for spatial disaggregation of CO 2 emission based on an assumed linear relationship between the digital number (DN) values of nighttime light imagery and the amount of CO 2 emissions. However, reliability of the linear relationship of these variables has not been thoroughly examined. In this study we find that the actual overall correlations are exponential rather than linear. More specific analyses showed that the DN values of nighttime light imagery first behaves linearly (from 3 to 50) and then exponentially (from 51 to 63), correlating to the amount of CO 2 emissions. Regardless of the use of a linear or piecewise function, some featured limitations are evident as we developed the methodology. Among significant limitations, CO 2 emissions were not visualized in unlit areas and a lack of variation existed in regions with the same DN values of nighttime light imagery. Lastly CO 2 emissions in urban core areas were grossly under-estimated.

data. Recent developments in unmanned aerial vehicle (UAV) technology provide cost effective and real time applications for site specific data collection. For the mapping of herbage biomass (BM) on a hill pasture, we tested a UAV system with digital cameras (visible and near-infrared (NIR) camera). The field measurements were conducted on the grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17 and June 27, 2014. Plant samples were obtained from 28 sites. A UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number (DN) values of Red and NIR channels were extracted from the aerial photos and a normalized differential vegetation index using DN (NDVIdn) was calculated. The results show that the correlation coefficient between BM and NDVIdn was 0.88. For the precision management of hilly grazing pastures, UAV monitoring systems can be a quick and cost effective tool to obtain site-specific herbage BM data.

Around the peaks of substantial flares, bright artifact nearly horizontal saturation streaks (B-streaks) corresponding to the brightest parts of the flare sources appear in the STEREO/EUVI 195 A images. We show that the length of such B-streaks can be used for the solution of an actual problem of evaluating the soft X-ray flux and class of far-side flares registered with double STEREO spacecraft but invisible from Earth. For this purpose from data on about 350 flares observed from January 2007 to July 2014 (mainly exceeding the GOES M1.0 level) both with GOES and STEREO, an empirical relation is established correlating the GOES 1-8 A peak flux and the B-streak length. This allowed us for the same years to estimate the soft X-ray classes for approximately 65 strong far-side flares observed by STEREO. The results of this simple and prompt method are consistent with the estimations of Nitta et al. (Solar Phys., 288, 241, 2013) based on the calculations of the EUVI full-disk digital number output. In addition, we studied some features of the B-streaks in impulsive and long-duration flares and demonstrated that B-streaks in several consecutive EUVI images can be used to reconstruct a probable time history of strong far-side flares., Comment: 16 pages, 7 figures, 2 tables. Submitted to Solar Physics

This chapter covers the processing of analog data by microcontroller by using analog-to-digital converters (ADCs). The environment present around the microcontroller is analog but the processing of data in the microcontroller is done on the digital data. So, ADCs are required to convert continuous analog voltage to discrete digital number which can be realized in digital form. The microcontroller has built in ADC modules. Since the conversion of analog to digital data is done on the basis of quantization, so some error will be introduced in the conversion due to quantization. This error cannot be eliminated though it can be decreased by increasing the number of bits of digital output.

Absolution radiometric calibration is the process of obtaining the relation between the at-sensor radiance and the pixel digital number recorded by the sensor. It is important to be able to calculate the radiance for every pixel in a satellite imagery, for comparison of data collected at different time, and for monitoring the radiometric stability of the sensor. We successfully performed radiometric calibration of TeLEOS-1 imaging sensor by inter-comparison with coincidental images collected by MODIS.

With the awareness of water quality degradation, people are eager to know quantitatively the quality of the water that they are drinking and whether the water is safe for human health or not. Government officials are also expecting a concise and unique guide to help them in water quality monitoring and management. However, performing a rational and quick assessment on water quality is always a challenge to water quality engineers and environmentalists due to the intrinsic complexity of the assessment. During the past several decades, numerous methods have been proposed for water quality assessment, however, still the most popular method is the use of water quality index (WQI) to make an assessment by translating large numbers of variables into a digital number. It is applied universally due to its intelligible concept and easy-to-operate procedure for water quality engineers. WQI has undergone significant development over the past several decades, but its advances have never been comprehensively reviewed. Water Quality Indices by Tasneem Abbasi and S.A. Abbasi is the first monograph that introduces the history, advances, application and future perspective of WQI in environmental science (Fig. 1). It describes the purpose of WQIs, their development, strengths and weaknesses. This excellent book will definitely be widely referenced by international scholars. Water Quality Indices is organized into three relatively concise parts. The first part consisting of 11 chapters focuses on the introduction and application of physicochemical parameter-based WQIs. Part II comprises four chapters introducing the WQI application integrated with P. Li (&) School of Environmental Science and Engineering, Chang’an University, No. 126 Yanta Road, Xi’an 710054, China e-mail: lipy2@163.com

A better understanding the effects of urbanization on vegetation is vital to promoting the sustainable development of cities in China, which has also experienced the world’s most remarkable urbanization during the past decades. This paper used satellite-derived night light, vegetation index, and socio-economic data to analyze spatio-temporal patterns of vegetation changes and evaluate the influence of urbanization on vegetation cover in 46 Chinese metropolises over the last four decades. To examine the effects of urbanization on vegetation and its valid distance, we proposed a new method of comparing three indicators, namely, annual average normalized difference vegetation index (NDVI), long-term trend of NDVI change and the proportion of pixels characterized by significant change in NDVI between built-up areas and its multiple buffer zones. The results showed that the effects of urbanization on vegetation have obvious spatial differences. Urbanization generally resulted in the decrease of vegetation coverage in built-up areas for most of China’s central and eastern metropolises, while in Western China, usually restricted by natural conditions, the urbanization usually improved vegetation coverage. The rates of increase in NDVI were significant lower than that of the buffer zones for most cities in central and eastern China. Urbanized areas of most cities located in central and eastern China had a higher percent of vegetation pixels, representing degradation than that in the buffer zones. The opposite was true for pixels representing vegetation restoration. The changes of NDVI in the cities in Western China were basically contrary to those in central and eastern China. The impacts of urbanization on vegetation are stage-specific. With the continuous progress of urbanization level, the adverse effect of urbanization on vegetation were gradually diminished or even disappeared. Cities with higher nighttime light levels appeared to have less vegetation coverage in the early years, and negative correlations between mean NDVI and the mean digital number value have become weak in more recent years. The changes in NDVI in urbanized areas of most cities significantly followed a ‘U’ shape. This phenomenon may further suggest that positive effects of urbanization become more obvious over time during advanced urbanization. The spatial scope of the impacts of urbanization on vegetation was beyond the urban built-up areas, and the effect intensity appeared to attenuate as the buffer distance became further away from the urbanized area. The valid distance of impacts of urbanization on vegetation is generally about 30–40 km.

Phenology is an important ecological indicator for understanding the feedback of plants to climate changes, but observation of plant phenology is not a trivial task, particularly for the large-scale areas of interest. Urban plant phenology monitoring is such a typical case, since massive residents do not necessarily mean enough eligible phenology observers. To handle this traditional challenge, this study attempted those surveillance cameras (SCs) widespread almost in any city all over the world. The schematic plan is to install an automatic software module, which has the function of plant phenology monitoring, as a plug-in into any central unit that wire-controls RGB SCs. The kernel of the module is a general-purposed algorithm capable of deriving the starting and ending dates of the key phenological events of different plants that stand in the field of view of each telecontrolled SC. The kernels of the algorithm comprise deriving phenological indices from the digital number (DN) records by a SC from all of its RGB channels and, then, modeling of plant dynamics based on the proposed novel phase-limited multi-Gaussian model for curve-fitting of phenological phases. In the case of determining the key phenological dates regarding flowering and foliation in this study, tests suggested that the proposed scheme and phenological indices and the programmed software plug-in all worked well. Overall, the feasibility of using the widespread SCs for urban plant phenology monitoring was validated, and the scheme can be further extended to composing phenology observation networks at local or global scales. The solution is of implications for more understanding the interannual rhythms of terrestrial ecosystems as well as the inherent mechanisms of vegetation-climate interactions.

LAPAN-A3/IPB Satellite is 3rd generation experimental satellite of LAPAN. This satellite has been launched in June 2016 and orbited on altitude 510km with sun synchronous orbit. One of the payloads of this satellite is experimental thermal imager camera, called micro-bolometer with 8-12 um band spectral. At first, micro-bolometer is used as horizon sensor, but also can be used for monitoring of earth surface temperature. The aim of this research is to validate image data of micro-bolometer based on Landsat infrared band image data. The method used in this research is to find the correlation between digital number (DN) of micro-bolometer camera of LAPAN-A3/IPB with the temperature that has been calculated and obtained from image of Landsat satellite. The result of this research shows that the data from micro-bolometer LAPAN-A3/IPB has characteristics that are close to Landsat infrared band image data. Moreover, the data of micro-bolometer camera has also been validated with multispectral camera of LAPAN-A3/IPB satellite both in coverage swath-width and visual identification.

Atmospheric correction is an essential process in quantitative remote sensing studies. There is lack of assessment of methods for coastal zone data, particularly historical data. In this study, the performances of existing methods are evaluated, with Jiangsu coastal zone, east China as the study area. Two methods, which are based on image acquisition date and on the maximal and minimal radiances, are used to convert digital number values to at-sensor radiance. The apparent reflectance method, and four image-based dark object subtraction (DOS) methods are used for correction of four historical thematic mapper (TM) images. The performances of these methods are evaluated by employing four assessment procedures. Results show that the method based on image acquisition date is superior to that based on the maximal and minimal radiances. Moreover, DOS-Iteration can achieve better results and can thus be a more reasonable correction model than the other methods.

Since economic reforms in 1978, China's huge growth has led to a rapid increase in demand for freight traffic. Timely assessments of past and current amounts of freight traffic are basis for predicting future demands of freight traffic and appropriately allocating transportation resources. Sum lights (summed digital number (DN) value of pixels of nighttime light imagery) for years 2000, 2004, and 2008 respectively are extracted from corresponding Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) stable lights annual image composites. The sum lights are then regressed on total freight traffic (TFT), railway freight traffic (RFT), and highway freight traffic (HFT), respectively, at the province level. Results show that sum light strongly correlates to TFT and HFT, so sum light can be used as a proxy for TFT and HFT at the province level. However, due to lack of strong correlations between RFT and GDP, sum light is not appropriate to be as a proxy of RFT. Finally we disaggregate each province/municipality's HFT to each pixel in proportion to the DN value of the pixel of the nighttime light image to produce a Chinese HFT map of 2008 with 1 km × 1 km resolution. Compared to traditional census-based freight traffic data, the freight traffic data derived from the nighttime light imagery contain more spatial information.

A thermal sensor is proposed for microprocessors, which compares the BJT voltage to a reference by converting both voltages to frequency and dividing the frequencies to result in a digital number. The sensor has an rms resolution of ±0.2C and an area of 0.02 mm2 at the 32-nm process node and 0.006 mm2 at 22 nm, including all digital processing circuitry. The conversion rate is between 2-20 kS/s, which enables it to capture fast transients on the CPU. It consumes 3.8/1.4 mW at 32/22 nm from an unregulated 1.4-V supply. The combination of speed, low power, and area make this sensor appropriate to measure hot-spots in microprocessors.

This paper takes advantage of the depth camera of somatosensory kinect and sensors to implement gesture recognition and design a virtual instrument system. As long as the user waves his arm without the help of other equipments, our system can automatically recognize the hand gesture and make suitable sound. In order to achieve depth camera’s detection of hands movement, this paper introduce the depth imaging technology Light Coding and bone tracking technology to obtain the actual position information and hand movement information of the human body. Feet movement detection uses sensor technology, different stampede strength outputs different digital number after AD conversion so that the intensity can be controlled. A series of experiments show that the system has good fluency and practicality and increased the fun of playing instruments.

The Hetian basinal area in County Changting of Fujian province is one of the most typical soil loss areas in the reddish soil regions of southern China.Local people and governments have been struggling for the control of the soil loss for decades.This study used remote sensing technology to analyze spatiotemporal dynamics of the bare soil cover in the Hetian basinal area since 1976.The bare soil features were extracted from the Landsat images of 1976,1988,1999,2004 and 2010 using two thematic indices-normalized difference soil index(NDSI) and normalized difference impervious surface index(NDISI).After converting the original digital number values of the images to at-satellite reflectance,the soil and impervious surface features were enhanced using the two indices,respectively.The soil features were then extracted from the soil-enhanced images.However,the extracted soil information was found to have been mixed with built-up land information due to the spectral confusion between the two categories.Therefore,the NDISI was further used to filter out the unwanted built-up land information from the soil images using a logical tree algorithm,as the NDISI is the index specially designed for highlight impervious surface features represented mainly by built-up lands.Results showed that the nearly thirty-five years of fight for controlling soil loss have greatly reduced bare soil covers in the basinal area.The area of the bare soil cover has been greatly reduced from 159.17 km2 in 1976 to 51.98 km2 in 2010.In the three observed periods,1976—1988,1988—1999,and 1999—2010,the decrease in bare soil cover was in an accelerate speed,which was-2.45 km2 per year,-2.75 km2 per year,and-4.33 km2 per year for the three periods,respectively.This corresponds to the major policies issued by the government for the soil loss treatment of the area.Government policies accompanied with effective actions have played a key role in the reducing of the bare soil cover in the Hetian basinal area.

Nocturnal lighting is directly related to human activity and has been used in modeling population density. Mismatch of spatial scale between county and pixel results in noticeable discrepancy in Digital Number (DN). Consequently, this paper focuses on the limitation and proposes a method to model population density using the DMSP-OLS night-time data. MODIS land cover product was employed to identify habitable area. Population density in habitable areas was simulated using mean DNs of night-time image and mean populations at county level so as to eliminate the discrepancy in DN. The Pearl River Delta of China is taken as study area. The accuracy of estimation was assessed with census data. The results indicated the proposed method has potential in estimating population density and differences among cities need to be considered in modeling.

Remote sensing is an effective technology for monitoring water resources. However, many methods in remote sensing imagery used to identify open bodies of water have often been shown to produce varying water body classification results for the same bodies of water. Therefore, it is necessary to have measures to assess these methods. In this study, we used datasets collected in the field to assess methods for identifying open water bodies using images from the Landsat 8 Operational Land Imager. From this, we clarified the difference in the performance between the use of spectral reflectance images and that of digital number (DN) value images for the classification of water bodies. The results showed that the normalized difference water index (NDWI), calculated using green and near-infrared bands (NDWIGreen/NIR) with reflectance, captured correct control points with an accuracy of greater than 95 % and was therefore the superior method. The result of a comparison in performance in terms of the NDWI between reflectance images and DN value images was consistent with their initial definitions. The NDWI indices calculated by the initial definitions yielded more reasonable results in the classification of water bodies. The optimized threshold, calibrated and validated by 737 field control points, generated water classification results with a higher confidence in this study. We think that it might be better to set the optimized threshold of NDWIGreen/NIR to −0.05 instead of the value of zero used in many studies. However, more optimized thresholds for other regions need to be calibrated and confirmed if data are available. Our results indicated that NDWI methods are more suitable for water body classification than single-band methods when the frequency histogram method is used.

The wide-view multispectral imager WVMI is the main instrument carried on an unmanned vehicle in the Unmanned Vehicle Payloads Comprehensive Calibration Campaign, which focuses on the calibration and validation of various remote-sensing sensors, including multispectral and hyperspectral sensors. In order to calibrate the WVMI, we designed and deployed a set of six radiometric calibration targets with nominal reflectances of 4%, 20%, 30%, 40%, 50%, and 60% and a set of four radiometric validation targets, the reflectance spectra of which vary dramatically with wavelength. The results reveal a good linear relationship between the digital number DN of each sensor and the apparent radiances. Further analysis of data from the validation targets reveals that both spectral unevenness and low reflectance will lead to incurrence of errors in calculations using the calibration equation. This suggests a potential problem that needs to be addressed in the remote sensing of vegetation.

Much effort has been spent on the automatic detection and delineation of individual trees from high spatial resolution images. However, delineation errors may lead to an inaccurate crown size when compared with ground measurements. Thus, it is problematic to use delineated crowns to derive information on tree variables, e.g. crown diameter, tree height, diameter at breast height DBH, stand volume, stem volume or stand competition index. In this study, we investigated two indicators – the mean digital number MDN within each delineated crown and the difference between MDNs DMDNs for 0.6 m buffer zones outside and inside the boundary of each delineated crown – to separate poorly delineated crowns from well-delineated ones. We modelled the relationships between delineated crowns and field-based crown size, between delineated crowns and tree height, and between delineated crowns and DBH observations in a Norway spruce Picea abies stand, separately considering models based on all delineated results and crowns identified as being well delineated. Our results showed that the capability of the two indicators in separating poorly and well-delineated crowns varied under different thresholds. The results also indicated that models considering only well-delineated crowns were more robust and effective in estimating and predicting tree crown diameter, DBH and tree height than models that considered all delineated results.

This study deals with an evaluation of the efficacy of an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image for lithological mapping. ASTER level-1B data in the visible near-infrared (VNIR), short wave infrared (SWIR) and thermal infrared (TIR) regions have been processed to generate a lithological map of the study area in and around the Phenaimata igneous complex, in mainland Gujarat, India. ASTER band combinations, band ratio images and spectral angle mapper (SAM) processing techniques were evaluated for mapping various lithologies. The reflectance and emissivity spectra of rock samples collected from the study area were obtained in the laboratory and were used as reference spectra for ASTER image analysis. The original data in the scaled digital number (DN) values were converted to radiance and then to relative reflectance by using a scene-derived correction technique prior to SAM classification. The SAM classification in the VNIR-SWIR region is found to be effective in differentiating felsic and mafic lithologies. The relative band depth (RBD) images were generated from the continuum-removed images of ASTER VNIR-SWIR bands. Four RBD combinations (3, 5, 6 and 8) were used to identify Al-OH (aluminium hydroxide), Fe-OH (iron hydroxide), Mg-OH (magnesium hydroxide) and CO(3) (carbonate) absorption from various lithological components. ASTER TIR spectral emittance data and the laboratory emissivity measurements show the presence of a number of discrete Si-O spectral features that can differentiate mafic and felsic rock types reflecting the lithological diversity around the regions of Phenaimata igneous complex. SAM classification using emittance data failed to distinguish the felsic and mafic lithology due to the wider spectral bandwidth. The felsic class comprises the granitoid composition of rocks. RBD12 and 13 images in the TIR region were used to derive the mafic index (MI) and the silica index (SI). The MI shows the highest value in regions of gabbro-basalt occurrence, while the SI indicates regions of high silica content. The MI is lowest in regions where granophyres occur. The complimentary attributes based on the spectral reflectance and emittance data resulted in the discrimination of silica-rich and silica-poor lithologies.

Time series monitoring of earthquake-stricken areas is significant in evaluating post-disaster reconstruction and recovery. The time series of nighttime light (NTL) data collected by the defense meteorological satellite program-operational linescan system (DMSP/OLS) sensors provides a unique and valuable resource to study changes in human activity (HA) because of the long period of available data. In this paper, the DMSP/OLS NTL images’ digital number (DN) is used as a proxy for the intensity of HA since there is a high correlation between them. The purpose of this study is to develop a methodology to analyze the changes of intensity and distribution of HA in different areas affected by a 2008 earthquake in Wenchuan, China. In order to compare the trends of HA before and after the earthquake, the DMSP/OLS NTL images from 2003 to 2013 were processed and analyzed. However, their analysis capability is greatly limited owing to a lack of in-flight calibration. To improve the continuity and comparability of DMSP/OLS NTL images, this study developed an automatic intercalibration method to systematically correct NTL data. The results reveal that: (1) compared with the HA before the earthquake, the reconstruction and recovery of the Wenchuan earthquake have led to a significant increase of HA in earthquake-stricken areas within three years after the earthquake; (2) the fluctuation of HA in a severely-affected area is greater than that in a less-affected area; (3) recovery efforts increase development in the most affected areas to levels that exceeded the rates in similar areas which experienced less damage; and (4) areas alongside roads and close to reconstruction projects exhibited increased development in regions with otherwise low human activity.

Rarefaction represents a powerful analytical approach in ecology for estimating the expected number of species within a given study area from local (α-diversity) to regional (γ-diversity) scales. From a landscape perspective, rarefaction curves are directly related to the environmental heterogeneity of the area sampled. The greater the landscape heterogeneity, the greater the expected species diversity. Therefore, remotely sensed images may potentially be used for predicting species diversity through the indirect method of analysing local spectral variation. The aim of this study was to test whether spectral variability can be used as a proxy for species diversity, from local to regional spatial scales. A total of 977 sampling units, each 50 m×50 m, were selected within the Asciano district (Central Italy) following a stratified random sampling. Each sampling unit was manually classified according to the first level of the Corine Land Cover classification legend. Data on plant species composition were collected in 10 m×10 m plots located within 98 random sampling units. The normalized difference vegetation index (NDVI) was calculated from a QuickBird image, and quantized into 8-bit data (256 digital numbers, DNs) for building spectral rarefaction curves. Only those plots falling within the QuickBird image were used, which had the effect of reducing the thematic legend to two classes: crops and seminatural vegetation. Species and spectral rarefaction curves were then constructed for each land cover class. Rarefaction curves based on species and spectral properties showed similar results, that is a significantly different number of accumulated values given the same sampling effort for the two classes considered. The results of this study suggest that the shape of the spectral rarefaction curves may be an indirect indicator of environmental diversity, and thus may have potential for predicting biodiversity from local to landscape scales.

Almost all conventional linear spectral unmixing techniques are based on the principle of least squares. The global mean digital number (DN) of an end-member is taken as the representative (i.e. contributory) DN for the end-member. This paper sets out to prove that the notion is a fallacy, and will always lead to negative percentages, super-positive percentages and non-100% sum of percentages if the unmixed pixel is not composed of, to within some tolerance, the global mean DNs only. Three sets of spectral end-members (two, three and four spectral end-members) are generated from Landsat ETM+ data. Practical percentages (between 0% and 100% and totalling 100%) of the end-members are returned by pixels in which the local mean DNs of the spectral end-members do not differ from the global mean DNs by, on average, 4.

This study investigated the potential of using remote sensing for mapping and monitoring of submerged aquatic vegetation (SAV) on a large scale. The spectral characteristics of SAV with varied coverage were measured using a portable spectroradiometer on a man-made lake at the Chongming International Wetland Park, Shanghai, China. A good relationship between the coverage of SAV and their field spectral characteristics was established and the reflectance of SAV increased with its increasing coverage. A regression analysis was then carried out between the coverage and the reflectance at the wavelengths of four QuickBird bands. After making an atmospheric correction from a synchronous QuickBird image for the study site, the image digital number (DN) was converted into the ground reflectance. The reflectance image was then deduced into a distribution map of SAV coverage by using the results of the regression functions between the coverage of SAV and the reflectance rate measured in situ . An accuracy assessment indicated that this approach could be used to quickly monitor the distribution and growth situation of SAV. The implications of this observation, in terms of the ability of remote sensing to estimate and monitor the distribution and dynamics of SAV on a large scale are discussed.

This research deals with the ripeness grading of oil palm fruit bunches. The current practice in the oil palm mills is to grade the oil palm bunches manually using human graders. This method is subjective and subject to disputes. In this research, we developed an automated grading system for oil palm bunches using the RGB color model. This grading system was developed to distinguish between the three different categories of oil palm fruit bunches. The maturity or color ripening index was based on different color intensity. Our grading system employs a computer and camera to analyze and interpret images equivalent to the human eye and brain. The colors namely Red, Green and Blue (RGB) of the palm oil fruit bunch were investigated using this grading system. The computer program developed and used the mean color intensity to differentiate between the different color and ripeness of the fruits such as oil palm FFB. The program results showed that the ripeness of fruit bunch could be differentiated between different categories of fruit bunches based on RGB intensity.

Detection of cyanbacteria blooms in Taihu using vegetation index data from MODIS was carried out since cyanbacteria blooms broke out in May 2007.The results showed that MODIS was able to detect cyanobacteria bloom effectively.Algorithm of band ratio between infrared and red band and values of NDVI or EVI can be used to analyze the distribution of algae.However,the former two were difficult to distinguish high-turbid water from algae or identify areas with low density of cyanbacteria,which resulted in the magnified or reduced areas of algae,while the latter one could constrain background noise properly mainly from water and suspended matter.Therefore,based on the digital number values(DNs)of EVI band,an approximately actual distribution of algae was induced.The study showed that satellite observations could be effectively applied to cyanobacteria bloom real-time monitoring system for Lake Taihu.

It is significant that remote sensing methods is used for monitoring cyanobacteria bloom in Lake Taihu,since it breaks out frequently each year.Based on spectral characters of cyanobacteria bloom,different algorithm including single band,band subtraction and band ratio,were used for bloom mapping,with different instruments such as the MODIS/Terra,CBERS-2 CCD,ETM and IRS-P6.They noted that all these sensors were able to detect cyanobacteria bloom,while the algorithm of band ratio between infrared and red band has a stable correlation with blooms,and it can be developed into a universal pattern.Except that,spatial cyanobacteria bloom concentrations were separated into five classes based on digital number values(DNs)in ETM and IRS-P6 Band 4.This study showed that satellite observations was effectively applied to cyanobacteria bloom monitoring and early-warning for Lake Taihu.

This paper proposes a method to support sugarcane yield forecast using vegetation spectral indices, principal component analysis and historic yield data. The study area is located in the State of Sao Paulo, Brazil, and is divided into 11 production plots (108.75 ha), where sugarcane of the RB85 5536 variety is cultivated on red latossol (oxissol‐type) soil and flat topography. The data employed in the study include radiometrically and geometrically corrected enhanced thermatic mapper Plus (ETM+)/Landsat‐7 and ASTER/Terra images, acquired in June and April 2001, respectively, and historic harvest data measured in 2000 and 2001. The method comprises several steps: (a) enhancement of specific spectral responses of vegetation constituents; (b) reduction of spectral dimensions with prioritization of information and weighing of parameters related to foliar area; the data processed through these steps are reduced to a single image (the synthesis image), from which the mean DN (digital number) per cultivated area...

A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band’s radiance (Lλ,L7/ETM+) to that of Landsat-5 TM TIR (Lλ,L5/TM) as: Lλ,L5/TM=0.9699xLλ,L7/ETM++0.1074 (R2=1). In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.