共查询到20条相似文献，搜索用时 93 毫秒
1.
Ashish Dhamaniya 《Journal of the Indian Society of Remote Sensing》2014,42(4):851-858
Present paper focuses on the development of a planning model for upgradation of rural roads keeping Pradhan Mantry Gram Sadak Yoyna (PMGSY) program as the base of this model. Database for the PMGSY roads of Gandevi block of Navasari district in Gujarat state is prepared which includes data like village data, road network & traffic data. Core network is prepared for all the villages under study which can be defined as rural network required for providing ‘basic accesses to all villages. i.e. all villages are connected nearby market centre and essential places from all weather roads. Planning model is classified in two phases. First phase is the network planning and the second phase is upgradation of roads. For the network planning utility values of the villages is calculated by using Delphi technique and on the basis of that alternative routes are decided. For the upgradation of existing roads, Pavement Condition Index (PCI) value of each road is determined and based on these values upgradation of roads are priorities. The rural road network planning methodology for PMGSY roads based on the accessibility concept is presented in this paper and implemented using Geographic Information System (GIS) technology. 相似文献
2.
The challenge of assessing and monitoring the influence of rangeland management practices on grassland productivity has been hampered in southern Africa, due to the lack of cheap earth observation facilities. This study, therefore, sought to evaluate the capability of the newly launched Sentinel 2 multispectral imager (MSI) data, in relation to Hyperspectral infrared imager (HyspIRI) data in estimating grass biomass subjected to different management practices, namely, burning, mowing and fertilizer application. Using sparse partial least squares regression (SPLSR), results showed that HyspIRI data exhibited slightly higher grass biomass estimation accuracies (RMSE = 6.65 g/m2, R2 = 0.69) than Sentinel 2 MSI (RMSE = 6.79 g/m2, R2 = 0.58) across all rangeland management practices. Student t-test results then showed that Sentinel 2 MSI exhibited a comparable performance to HyspIRI in estimating the biomass of grasslands under burning, mowing and fertilizer application. In comparing the RMSEs derived using wave bands and vegetation indices of HyspIRI and Sentinel, no statistically significant differences were exhibited (α = 0.05). Sentinel (Bands 5, 6 and 7) and HyspIRI (Bands 730 nm, 740 nm, 750 nm, 710 nm), as well as their derived vegetation indices, yielded the highest predictive accuracies. These findings illustrate that the accuracy of Sentinel 2 MSI data in estimating grass biomass is acceptable when compared with HyspIRI. The findings of this work provide an insight into the prospects of large-scale grass biomass modeling and prediction, using cheap and readily available multispectral data. 相似文献
3.
Land surface temperature (LST) is an important aspect in global to regional change studies, for control of climate change and balancing of high temperature. Urbanization is one of the influencing factors increasing land surface and atmospheric temperature, by the emission of greenhouse gases (e.g. CO2, NO and methane). In the present study, LST was derived from Landsat-8 of multitemporal data sets to analyse the spatial structure of the urban thermal environment in relation to the urban surface characteristics and land use–land cover (LULC). LST is influenced by the greenhouse gases i.e. CO2 plays an important role in increasing the earth’s surface temperature. In order to provide the evidence of influence of CO2 on LST, the relationship between LST, air temperature and CO2 was analysed. Landsat-8 satellite has two thermal bands, 10 and 11. These bands were used to accurately to calculate the temperature over the study area. Results showed that the strength of correlation between ground monitoring data and satellite data was high. Based on correlation values of each month April (R2 = 0.994), May (R2 = 0.297) and June (R2 = 0.934), observed results show that band 10 was significantly correlating with air temperature. Relationship between LST and CO2 levels were obtained from linear regression analysis. band 11 was correlating significantly with CO2 values in each of the months April (R2 = 0.217), May (R2 = 0.914) and June, (R2 = 0.934), because band 11 is closer to the 15-micron band of CO2. From the results, it was observed that band 10 can be used for calculating air temperature and band 11 can be used for estimation of greenhouse gases. 相似文献
4.
Yanfang Ming Lijuan Cheng Huiyong Yu Chunxiang Wang 《Journal of the Indian Society of Remote Sensing》2018,46(1):69-79
This study investigates the applicability of estimating chlorophyll and water content at canopy level through empirical models and band combinations. The main goal is to evaluate and compare the accuracy of these two approaches for estimating and mapping canopy chlorophyll and water content through canopy reflectance and spaceborne HJ1-A HSI data acquired over Yanzhou coal mining area. An experiment was carried out. Canopy spectral measurements were acquired in the field using an ASD spectroradiometer along with simultaneous in situ measurements of leaf chlorophyll content. We tested seven variables derived from canopy reflectance for detecting canopy chlorophyll and water content: (1) R, (2) Log(1/R), (3) Log(1/R)′, (4) FDR, (5) SDR, (6) CRR, (7) BD. Stepwise multiple linear regressions were used to select wavelengths from HJ1-A HSI image bands. Correlation analysis was also done between different band combinations and biochemistry. A statistically significant relationship between Log(1/R) and chlorophyll was found at canopy level (R2 = 0.516). SDR had the highest correlation with canopy water content (R2 = 0.490). In addition, relationship between normalized different band combinations and chlorophyll and water content is also significantly obvious (R2 = 0.577 and R2 = 0.615). Canopy chlorophyll content was estimated with the intermediate accuracy (R2 = 0.4144), while water content was estimated with an acceptable accuracy (R2 = 0.4592). Canopy chlorophyll and water content spatial distribution were mapped. Chlorophyll and water stress levels were quantified by comparing different environmental stressors. 相似文献
5.
Water quality problems continue on a global scale and this creates the need for regular monitoring using cheaper technologies to inform management. The objective of this study was to test for significant relationships between the field-measured and Landsat 8 OLI sensor-retrieved water quality parameters. The study was carried out in two reservoirs with contrasting trophic states in Zimbabwe. Results show that the Blue/Red ratio had strong predictive relationships with Secchi disc transparency (R2 > 0.70) and turbidity (R2 ≥ 0.65). The Near-infrared/Red ratio was a strong predictor of chlorophyll-a in Mazvikadei (R2 > 0.84) whereas in Lake Chivero, which is more polluted, the red band was the most useful predictor (R2 = 0.69). Overall, our work demonstrates the utility of using Landsat 8 band ratios for remote assessment of water quality in African reservoirs as a value-addition to the traditional field-based methods, which are expensive resulting in data scarcity. 相似文献
6.
Remote sensing is useful for water quality assessments but current remote sensing applications favour parameters that are easy to detect such as chlorophyll-a. An assessment of the utility of Landsat 8 for detecting nutrients was conducted in Mazvikadei reservoir in Zimbabwe. The main objective was to determine whether nutrients often overlooked by remote sensing and yet are the main determinants of water quality can be remotely sensed. Sampling targeted ammonia, nitrates and reactive phosphorus from May to October 2015. In situ nutrient concentrations were regressed against reflectance derived from Landsat 8 imagery. Strong negative relationships were found between ammonia and the near-infrared band in July (R2 = 0.80, p < 0.05) as well as between nitrates and the blue band (R2 = 0.67, p < 0.05) in June. Overall, the results suggest that the cool dry season is the optimum time to use Landsat 8 for monitoring nutrients in tropical lakes. 相似文献
7.
Hassan M. Fadul Ahmed A. Salih Imad-eldin A. Ali Shinobu Inanaga 《International Journal of Applied Earth Observation and Geoinformation》1999,1(3-4)
The problems and impact of gully erosion along the Atbara River (Sudan), situated in semi-arid and arid environments, were investigated. The total gross area of gullied land and the loss of arable land by gully erosion were estimated. Multi-date sets of panchromatic aerial photographs and Landsat images (TM) were selected to represent two sites in the arid (New Halfa) and semi-arid (Showak town) zones along the Atbara River. Photo interpretation was conducted using physiographic and element methods. The interpretations detected the effects of water action in different climatic zones on geology, lithology, vegetation and land use. The results showed that the traditional rainfed agriculture has accelerated gully erosion in the semi-arid rather than in the arid zone. The progressive rate of gully erosion in the semi-arid zone resulted in loss of arable land at about 13.4 km2 yr-1 and 9.8 km2 yr-1 in the periods 1985–1987 and 1987–1990, respectively. The study provided data on the monitoring and mapping of gully erosion along the Atbara River and its tributaries. 相似文献
8.
Mohamed E. Hereher 《国际地球制图》2017,32(5):556-568
Cairo region is characterized by a range of physiographic features, including: flat agricultural lands, bare sandy deserts, highlands, calcareous terrains and urban land use. A time series data-set (300 images) acquired from the Moderate Resolution Imaging Spectroradiometer for the period July 2002–June 2015 were utilized to retrieve the spatial variations in the mean land surface temperature (LST) for the above-mentioned surface features. Results showed that vegetation, topography and surface albedo have negative correlations with LST. Vegetation/LST correlation has the maximum regression coefficient (R2 = 0.68) and albedo/LST has the minimum (R2 = 0.03). Cultivated lands reveal the lowest mean LST (<32 °C), whereas industrial lands exhibit the highest LST (>40 °C) of Cairo region. There is a considerable urban heat island formed at Helwan south of Cairo, where heavy industries are settled. Industrial activities raised the mean LST of the region by at least 4 °C than the surrounding urban lands. 相似文献
9.
This study tested the use of machine learning techniques for the estimation of above-ground biomass (AGB) of Sonneratia caseolaris in a coastal area of Hai Phong city, Vietnam. We employed a GIS database and multi-layer perceptron neural networks (MLPNN) to build and verify an AGB model, drawing upon data from a survey of 1508 mangrove trees in 18 sampling plots and ALOS-2 PALSAR imagery. We assessed the model’s performance using root-mean-square error, mean absolute error, coefficient of determination (R2), and leave-one-out cross-validation. We also compared the model’s usability with four machine learning techniques: support vector regression, radial basis function neural networks, Gaussian process, and random forest. The MLPNN model performed well and outperformed the machine learning techniques. The MLPNN model-estimated AGB ranged between 2.78 and 298.95 Mg ha?1 (average = 55.8 Mg ha?1); below-ground biomass ranged between 4.06 and 436.47 Mg ha?1 (average = 81.47 Mg ha?1), and total carbon stock ranged between 3.22 and 345.65 Mg C ha?1 (average = 64.52 Mg C ha?1). We conclude that ALOS-2 PALSAR data can be accurately used with MLPNN models for estimating mangrove forest biomass in tropical areas. 相似文献
10.
Salting operations are essential but expensive in northern winters. We aim to predict the quantity of salt and abrasive needed for a specific road segment for each hour. An estimate of the quantity allows managers to better manage the loads in the trucks and to propose optimal vehicle routes based on the forecast, which will allow them to optimize costs. This article uses machine‐learning techniques based on truck telemetry data, weather conditions, and segment attributes. Geographic information systems (GIS) allow us to exploit the street‐network characteristics, which were ignored by previous prediction models. The results show that the XGBoost method performs better than other techniques (R2 = 0.83). 相似文献
11.
Spatiotemporal changes of urban impervious surface area and land surface temperature in Beijing from 1990 to 2014 总被引：1，自引：0，他引：1
This study examined changes in urban expansion and land surface temperature in Beijing between 1990 and 2014 using multitemporal TM, ETM+, and OLI images, and evaluated the relationship between percent impervious surface area (%ISA) and relative mean annual surface temperature (RMAST). From 1990 to 2001, both internal land transformation and outward expansion were observed. In the central urban area, the high-density urban areas decreased by almost 7 km2, while the moderate- and high-density urban land areas increased by 250 and 90 km2, respectively, outside of the third ring road. From 2001 to 2014, high-density urban areas between the fifth and sixth ring roads experienced the greatest increase by more than 210 km2, and RMAST generally increased with %ISA. During 1990–2001 and 2001–2014, RMAST increased by more than 1.5 K between the south third and fifth ring roads, and %ISA increased by more than 50% outside of the fifth ring road. These trends in urban expansion and RMAST over the last two decades in Beijing can provide useful information for urban planning decisions. 相似文献
12.
High-data dimensionality is a common problem in hyperspectral data processing. Consequently, remote sensing techniques that reduce the number of bands are considered essential tools for most hyperspectral applications. The aim of this study was to examine the utility of the random forest ensemble to select the optimal subset of hyperspectral bands to predict the age of Pinus patula stands. Airborne AISA Eagle hyperspectral image data were collected over the study area. The random forest ensemble was used to test whether the forward or backward variable selection methods could identify the optimal subset of bands. Results indicate that both the selection methods produced high-predictive accuracies (root mean square error = 3.097 years). However, the backward variable selection method utilized 206 bands for the final model, while the forward variable selection utilized only a small subset of non-redundant bands (n = 9) while preserving the highest model accuracy (R 2 = 0.6). 相似文献
13.
An automatic fractional vegetation cover (FVC) estimation method based on image characteristics in an agricultural region was proposed in this study to remove the empiricism in determining the key parameters of empirical methods. The proposed method automatically determined the soil and vegetation lines in the two-dimensional space of the red and blue band reflectances, which involved an iterative soil and vegetation pixels selection procedure, and then estimated FVC of a pixel based on its distances from the soil and vegetation lines. The accuracy assessment using field survey data indicated that the performance of the proposed method (R2 = 0.69, RMSE = 0.072, Bias = 0.014) was comparable with several commonly used empirical methods. Therefore, it was indicated that the proposed method could effectively estimate FVC in the corn-dominated region. 相似文献
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15.
GIS技术在道路选线中的应用 总被引：5，自引：0，他引：5
针对传统道路选线方法所具有的精度不高、效率低下和绘图周期长等缺陷,以及现行CAD技术不能解决线路比选等问题,引入地理信息系统的有关理论、方法和技术分析手段,利用GeoStar系列软件,对道路选线过程中所出现的若干问题进行分析研究,从而提出一种全新的道路选线方法。 相似文献
16.
东北黑土区侵蚀沟遥感影像特征提取与识别 总被引：3，自引：0，他引：3
东北黑土区是中国重要的粮食生产区,而长期的开垦造成了严重的水土流失现象,坡耕地表面出现大量的侵蚀沟。侵蚀沟的识别是土壤侵蚀监测的重要手段之一,目前遥感技术在侵蚀沟的识别中应用广泛,但自动化程度不高。针对特定地物影像的识别,如何选取最能够有效描述该地物的特征是解决问题的关键。本文构建了耕地和侵蚀沟遥感影像的训练样本集,基于样本集分别提取了由光谱特征和纹理特征组成的浅层特征、SIFT特征经编码后得到的中层特征,以及利用卷积神经网络提取的深层特征;再基于不同层次的特征选用合适的分类器对遥感影像进行分类,识别出含有侵蚀沟的遥感影像,形成了一套针对侵蚀沟的特征提取与识别方法,为东北黑土区的耕地保护提供有力支持。测试结果表明:基于中层特征的识别精度最高,为98.5%,但该特征需要人工设计,自动化程度有限;而利用卷积神经网络可自动提取深层特征,其识别精度达到了95.5%,同时大大提高了自动化程度,满足侵蚀沟影像的识别的需求。 相似文献
17.
Detection of crop water stress is crucial for efficient irrigation water management. Potential of Satellite data to provide spatial and temporal dynamics of crop growth conditions makes it possible to monitor crop water stress at regional level. This study was conducted in parts of western Uttar Pradesh and Haryana. Multi-temporal Landsat data were used for detecting wheat crop water stress using vegetation indices (VIs), viz. vegetation water stress index (VWSI) and land surface wetness index water stress factor (Ws_LSWI). The estimated water stress from satellite data-based VIs was validated by water stress factor (Ws) derived from flux-tower data. The study observed Ws_LSWI to be better index for water stress detection. The results indicated that Ws_LSWI was superior over other index showing RMSE = 0.12, R2 = 0.65, whereas VWSI showed overestimated values with mean RD 4%. 相似文献
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19.
Jorge Andres Morandé Christine M. Stockert Garrett C. Liles John N. Williams David R. Smart Joshua H. Viers 《Carbon balance and management》2017,12(1):5
Background
Quantifying terrestrial carbon (C) stocks in vineyards represents an important opportunity for estimating C sequestration in perennial cropping systems. Considering 7.2 M ha are dedicated to winegrape production globally, the potential for annual C capture and storage in this crop is of interest to mitigate greenhouse gas emissions. In this study, we used destructive sampling to measure C stocks in the woody biomass of 15-year-old Cabernet Sauvignon vines from a vineyard in California’s northern San Joaquin Valley. We characterize C stocks in terms of allometric variation between biomass fractions of roots, aboveground wood, canes, leaves and fruits, and then test correlations between easy-to-measure variables such as trunk diameter, pruning weights and harvest weight to vine biomass fractions. Carbon stocks at the vineyard block scale were validated from biomass mounds generated during vineyard removal.Results
Total vine C was estimated at 12.3 Mg C ha?1, of which 8.9 Mg C ha?1 came from perennial vine biomass. Annual biomass was estimated at 1.7 Mg C ha?1 from leaves and canes and 1.7 Mg C ha?1 from fruit. Strong, positive correlations were found between the diameter of the trunk and overall woody C stocks (R2 = 0.85), pruning weights and leaf and fruit C stocks (R2 = 0.93), and between fruit weight and annual C stocks (R2 = 0.96).Conclusions
Vineyard C partitioning obtained in this study provides detailed C storage estimations in order to understand the spatial and temporal distribution of winegrape C. Allometric equations based on simple and practical biomass and biometric measurements could enable winegrape growers to more easily estimate existing and future C stocks by scaling up from berries and vines to vineyard blocks.20.
Heather J. Richardson David J. Hill Dan R. Denesiuk Lauchlan H. Fraser 《地理信息系统科学与遥感》2017,54(4):573-591
We used geographic datasets and field measurements to examine the mechanisms that affect soil carbon (SC) storage for 65 grazed and non-grazed pastures in southern interior grasslands of British Columbia, Canada. Stepwise linear regression (SR) modeling was compared with random forest (RF) modeling. Models produced with SR performed better than those produced using RF models (r2 = 0.56–0.77 AIC = 0.16–0.30 for SR models; r2 = 0.38–0.53 and AIC = 0.18–0.30 for RF models). The factors most significant when predicting SC were elevation, precipitation, and the normalized difference vegetation index (NDVI). NDVI was evaluated at two scales using: (1) the MOD 13Q1 (250 m/16-day resolution) NDVI data product from the moderate resolution imaging spectro-radiometer (MODIS) (NDVIMODIS), and (2) a handheld multispectral radiometer (MSR, 1 m resolution) (NDVIMSR) in order to understand the potential for increasing model accuracy by increasing the spatial resolution of the gridded geographic datasets. When NDVIMSR data were used to predict SC, the percentage of the variance explained by the model was greater than for models that relied on NDVIMODIS data (r2 = 0.68 for SC for non-grazed systems, modeled with SR based on NDVIMODIS data; r2 = 0.77 for SC for non-grazed systems, modeled with SR based on NDVIMSR data). The outcomes of this study provide the groundwork for effective monitoring of SC using geographic datasets to enable a carbon offset program for the ranching industry. 相似文献