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1.
马利群  李理  刘俊杰  孙九林  秦奋 《测绘科学》2021,46(3):80-86,95
针对GLAS地学激光测高系统是冰、云和陆地高程卫星(ICESat)的唯一监测工具,能够记录地表光斑内的地物信息,是否能应用于黄土高原土地覆盖分类的问题进行了研究。利用粒子群和最小二乘法相结合的方法对GLAS波形数据进行高斯分解,获取高斯波个数、波形总能量、波形信号起始和信号结束位置4个波形参数;基于波形自动分类方法对黄土高原水体、森林、城市用地、其他地类(裸地、低矮植被等)进行分类。通过基于覆盖相同研究区域的30 m地表覆盖数据(Globe Land30),验证分类的准确性。结果表明,GLAS大光斑波形数据对黄土高原的4种地类能够很好地进行区分,总分类精度高达87.68%,Kappa系数为65.79%。研究表明,GLAS波形数据可以作为获取土地覆盖信息的有效数据源,为研究黄土高原土地覆盖变化提供更丰富的数据支持。  相似文献   

2.
This article presents the use of kernel functions in fuzzy classifiers for an efficient land use/land cover mapping. It focuses on handling mixed pixels obtained from a remote sensing image by considering non-linearity between class boundaries. It uses kernel functions combined with the conventional fuzzy c-means (FCM) classifier. Kernel-based fuzzy c-mean classifiers were applied to classify AWiFS and LISS-III images from Resourcesat-1 and Resourcesat-2 satellites. Optimal kernels were obtained from eight single kernel functions. Fractional images generated from high resolution LISS-IV image were used as reference data. Classification accuracy of the FCM classifier increased with 12.93%. Improvement in overall accuracy shows that non-linearity in the dataset was handled adequately. The inverse multiquadratic kernel and the Gaussian kernel with the Euclidean norm were identified as optimal kernels. The study showed that overall classification accuracy of the FCM classifier improved if kernel functions were included.  相似文献   

3.
Assessment of area under agroforestry in Tehri district of North Western Himalaya, Uttarakhand, India has been done using GIS and remote sensing technology. The study district characterized by hilly terrain with varying elevations from 288 m to more than 2800 m and generally gentle slopes, valleys, flat land covers and agricultural terraces. High-resolution satellite imageries (spatial resolution 5.8 m) were used in this study for land uses and land covers classification. According to unsupervised classification, highest area was found under forest class (65.22%) followed by cropland (20.41%). Considerable area was also found under snow cover (9.45%) in the district. Area under agroforestry was estimated to be 5572.26 ha (1.53%) by this method, whereas it was estimated to be 7029.06 ha (1.93%) by supervised classification. Estimated cropland area comes out to be about 20.0%. An accuracy of 86.5% was found in this classification for agroforestry class. Highest area under agroforestry of 3707.36 ha was obtained in 1200–2000 m elevations followed by 2231.26 ha in 288–1200 m elevations. Negligible area was found on high elevation zones of more than 2800 m. The major agroforestry systems of dominated by Grewia oppositifolia (Bhimal), Celtis australis (Kharik) and Quercus leucotrichophora (Banj) were identified and mapped and remaining systems were grouped as others class. Estimated area under G. oppositifolia, C. australis and Q. leucotrichophora based systems come out to be 2330.82, 1456.80 and 1129.10 ha, respectively. These systems are multiple usufructs are food, fuelwood, fodder, fiber and small timber. It has been observed from the accuracy assessment that the estimates of area under agroforestry obtained under this study are reliable.  相似文献   

4.
Soil moisture estimation from satellite earth observation has emerged effectively advantageous due to the high temporal resolution, spatial resolution, coverage, and processing convenience it affords. In this paper, we present a study carried out to estimate soil moisture level at every location within Enugu State Nigeria from satellite earth observation. Comparative analysis of multiple indices for soil moisture estimation was carried out with a view to evaluating the robustness, correlation, appropriateness and accuracy of the indices in estimating the spatial distribution of soil moisture level in Enugu State. Results were correlated and validated with In-Situ soil moisture observations from multi-sample points. To achieve this, the Topographic Wetness Index (TWI), based on digital elevation data, the Temperature Vegetation Dryness Index (TVDI) and an improved TVDI (iTVDI) incorporating air temperature and a Digital Elevation Model (DEM) were calculated from ASTER global DEM and Landsat images. Possible dependencies of the indices on land cover type, topography, and precipitation were explored. In-Situ soil moisture data were used to validate the derived indices. The results showed that there was a positive significant relationship between iTVDI versus TVDI (R = 0.53, P value < 0.05), while in iTVDI versus TWI (R = 0.00, P value > 0.05) and TVDI versus TWI (R = ?0.01, P value > 0.05) no significant relationship existed. There was a strong relationship between iTVDI and topography, land cover type, and precipitation than other indices (TVDI, TWI). In situ measured soil moisture values showed negative significant relationship with TVDI (R = ?0.52, P value < 0.05) and iTVDI (R = ?0.63, P value < 0.05) but not with TWI (R = ?0.10, P value > 0.05). The iTVDI outperformed the other two index; having a stronger relationship with topography, precipitation, land cover classes and soil moisture. It concludes that although iTVDI outperformed other indices (TVDI, TWI) in soil moisture estimation, the decision of which index to apply is dependent on available data, the intent of usage and spatial scale.  相似文献   

5.
波形激光雷达传感器所获取的遥感数据几乎可以提供后向散射信号的全部特征,除了距离观测值,需要通过进一步分析接收的脉冲获取更多关于地表实体的物理特性,因此,这些相关的物理特性成为研究地表覆盖的新领域。通过总结利用波形信号处理技术进行地表覆盖解译工作的研究进展,开展了南极查尔斯王子山脉地区地表覆盖分类工作。首先,描述了GLAS的数据结构;其次,总结了相关的信号处理技术;然后,从实际应用角度讨论了方法的可用性;最后,以南极查尔斯王子山脉地区为例,实践了基于ICESat GLAS完整波形信号处理技术的地表覆盖分类方法。  相似文献   

6.
Our study examines the relationships among various environmental variables in Surat city using remote sensing. Landsat Thematic Mapper satellite data were used in conjugation with geospatial techniques to study urbanization and correlation among satellite-derived biophysical parameters namely, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), normalized difference bareness index (NDBaI) and land surface temperature (LST). A modified NDWI (MNDWI) was used for extracting areas under water. Land use/land cover classification was performed using hierarchical decision tree classification technique using ERDAS IMAGINE Expert classifier with an accuracy of 90.4% for 1990 and 85% for 2009. It was found that city has expanded over 42.75 sq.km within two decades. Built-up, fallow and sediment land use classes exhibited high dynamics with increase of nearly 200% and 50% and decrease of 55% respectively from 1990 to 2009. Vegetation and water classes were less dynamic with 20% decrease and 15% increase. The transformation of land parcels from vegetation to built-up, vegetation to fallow and fallow to built-up has resulted in increase of LST by 5.5 ± 2.6°C, 6.7 ± 3°C and 3.5 ± 2.9°C, respectively.  相似文献   

7.
Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land.  相似文献   

8.
Accurate simulation of rice yield is very important and vital for agriculture and food security. This study has analyzed the applicability of the RS-P-YEC (the remote-sensing-photosynthesis-yield estimation for crops) model for the rice yield simulation of the Middle and Lower Reaches of Yangtze River (MLRYR) in China. The simulated rice yield was compared with the actual statistical dataset, so as to obtain the accuracy of the model results. The results showed that the correlation coefficients (R) between simulated rice yield and statistical data is 0.708 (P < 0.01), the average relative errors were 9, 6.5, 7.2 %, and the root mean square errors were 777.5, 606.4, 693.4 kg/ha in 2007, 2008 and 2009, respectively. It indicated that the RS-P-YEC model can be used to estimate rice yield in the MLRYR region of China.  相似文献   

9.
Considering the contribution of the hardware biases to the estimated clock errors, an improved method for estimating the satellite inter-frequency clock bias (IFCB) is presented, i.e., the difference in the satellite clock error as computed from ionospheric-free pseudorange and carrier phase observations using L1/L2 and P1/P2 versus L1/L5 and P1/P5. The IFCB is composed of a constant and a variable part. The constant part is the inter-frequency hardware bias (IFHB). It contains the satellite and receiver hardware delays and can be expressed as a function of the DCBs [DCB (P1 ? P2) and DCB (P1 ? P5)]. When a reference satellite is selected, the satellite IFHB can be computed but is biased by a reference satellite IFHB. This bias will not affect the utilization of IFCB in positioning since it can be absorbed by the receiver clock error. Triple-frequency observations of 30 IGS stations between June 1, 2013, and May 31, 2014, were processed to show the variations of the IFHB. The IFHB values show a long-term variation with time. When a linear and a fourth-order harmonic function are used to model the estimated IFCB, which contains contributions of the hardware delays and clock errors, the results show that 89 % of the IFCB can be corrected given the current five triple-frequency GPS satellites with the averaged fitting RMS of 1.35 cm. Five days of data are processed to test the estimated satellite clock errors using the strategy presented. The residuals of P1/P5 and L1/L5 have a STD of <0.27 m and 0.97 cm, respectively. In addition, most predicted satellite IFCBs reach an accuracy of centimeter level and its mean accuracy of 5 days is better than 7 cm.  相似文献   

10.
中国南方森林冠顶高度Lidar反演—以江西省为例   总被引：1，自引：0，他引：1  
董立新  李贵才  唐世浩 《遥感学报》2011,15(6):1308-1321
激光雷达(Lidar)与光学遥感的有效结合对中国南方区域森林冠顶高度反演意义重大,而国产卫星将为中国森林生态研究提供新的数据源。本文联合利用大脚印激光雷达GLA和国产MERSI数据,在实现GLAS波形数据处理和不同地形条件下森林冠顶高度反演算法基础上,建立了区域尺度不同森林类型林分冠顶高度GLAS+MERSI联合反演关系模型,进行了江西地区森林冠顶高度反演。总体上,GLAS激光雷达森林冠顶高度估算精度较高;且在与MERSI 250 m数据的联合反演模型中,针叶林模型精度较好(R2=0.7325);阔叶林次之(R2=0.6095);混交林较差(R2=0.4068)。分析发现,考虑了光学遥感生物物理参数的GLAS+MERSI联合关系模型在区域森林冠顶高度估算中有较高精度,且在空间分布上与土地覆盖数据分布特征非常一致。  相似文献   

11.
Land-use change and Land-cover classes in Garur Ganga watershed of Bageshwar district in Uttranchal State during the periods 1963–1996 and 1986–1996 were analyzed through Survey of India Topographical Sheet and visual interpretation of LANDSAT 5 TM image bands 2, 3 and 4 using Geographical Information System (GIS). The detailed analysis have revealed that the area under agriculture and settlement increased from 34.98 to 42.34%. whereas the forest and barren land show a declining trend. Expansion of agriculture land and builtup areas have been found to be maximum in the 1200–1600 m elevation zone with 7–14° slope class. The loss of vegetation cover has been estimated to be 5.07% between 1963-1996 and 0.81% between 1986–1996.  相似文献   

12.
An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data   总被引：1，自引：0，他引：1  
This study investigated an appropriate method for soil moisture retrieval from radar images and coincident ground measurements acquired over bare soil and sparsely vegetated regions. The adopted approach based on a single scattering integral equation method (IEM) was developed to establish the relationship between backscatter coefficient and surface soil parameters including volumetric soil moisture content and surface roughness. The performance of IEM in 0–7.6 cm is better than that in 0–20 cm. Moreover, IEM can simulate correctly the backscatter coefficients only for the root mean square (RMS) height s < 1.5 cm at C-band and s < 2.5 cm at L-band by using an exponential correlation function and for s > 1.5 cm at C-band and s > 2.5 cm at L-band by using Gaussian function. However, due to the difficulties involved in the parameterization of soil surface roughness, the estimated accuracy is not satisfactory for the inversion of IEM. This paper used a combined roughness parameter and Fresnel reflection coefficient to develop an empirical model. Simulations were performed to support experimental results and to highlight soil moisture content and surface roughness effects in different polarizations. Results showed that a good agreement was found between the IEM simulations and the SAR measurements over a wide range of soil moisture and surface roughness characteristics. The model had a significant operational advantage in soil moisture retrieval. The correlation coefficients were 77.03 % at L-band and 81.45 % at C-band with the RMSEs of 0.515 and 0.4996 dB, respectively. Additionally, this work offered insight into the required application accuracy of soil moisture retrieval at a large area of arid regions.  相似文献   

13.
Land is the basic resource that is needed by man in order to survive: It provides humans with living space, nutrition and energy resources. The rapid growth of the human population, climate change and pollution on a catastrophic scale has caused the quality of land resources to be compromised. Remote sensing is a useful tool in land cover change detection providing information to decision makers. The aim of this study was to evaluate land cover changes in the Mtunzini area in South Africa over the past 18 years; determine why changes have occurred and predict land cover patterns for future years. In this study a supervised classification was used to detect land cover classes of the Mtunzini area from 1992 to 2009 using four Landsat images in the time series analysis. The supervised classification had an accuracy of 80.80 % which was used to model land cover changes. Commercial sugar cane and forest plantation classes increased throughout the time series. It was estimated in the modelling procedure that bushland (42.11 %) and bare soil (35 %) would be changed to commercial sugar cane. This is indicative of the expanding agriculture sector in Mtunzini. Natural vegetation is predicted to be disturbed: 18 % of bushland and 15.07 % of dense bush are expected to be replaced by rural dwellings. This is owing to a potential increase in the rural population and a reduced local economic growth. This study highlights the need for increased vigilance of the forestry industry and commercial sugar cane farms which may be encroaching on natural vegetation and livelihoods of local residents. Strategic planning and proper management of natural vegetation types is needed as these land cover types are decreasing rapidly.  相似文献   

14.
Cotton aphid (Aphis gossypii) is considered as one of the most important agriculture pest for the cotton production. However, it is generally labor-intensive and time-consuming to obtain some information of Cotton aphid with conventional methods through direct measurement by sampling in the field. This study explores the potential of using a new method to obtain information of the Cotton aphid rapidly. In our study, the cotton canopy spectral indices (NDVI, VI_2, REDrefc, NIRrefc) and chlorophyll concentration, obtained from hand-held high spectrometer GreenSeeker and chlorophyll meter SPAD-502 and Cotton aphid amount derived from the artificial field-based survey were used to uncover the relationship between Cotton aphid amount and canopy spectral index and SPAD value of the cotton in city of Shihezi, China. The results showed that NDVI and NIRrefc were negatively related to Cotton aphid amount. VI_2 content had a significant and positive relationship with its amount. The non-linear three cubic models with alate Aphid amount as independent variables have been established between VI_2 value and alatae Aphid amount, which could explain 92.37 % of VI_2 value variance. SPAD values were also significantly and negatively correlated to the Aphid amount. The non-linear logarithm model with wingless Aphid amount as independent variables was the best for uncovering the relationship between SPAD value and wingless Aphid amount, which could explain 85.48 % of SPAD value variance. The results demonstrate the establishment of the function model provides a theoretical basis and techniques for indirect and rapid monitoring and management of Cotton aphid.  相似文献   

15.
High spatial resolution satellite data contribute to improving land cover/land use (LCLU) classification in agriculture. A classification procedure based on Quickbird satellite image data was developed to map LCLU of diversified agriculture at sub-communal and communal level (7 km2). Segmentation performance of the panchromatic band in combination with high pass filters (HPF) was tested first. Accuracy of field boundary delineation was evaluated by an object-based segmentation, a per-field and a manual classification, along with a quantitative accuracy assessment. Sub-communal classification revealed an overall accuracy of 84% with a κ coefficient of 0.77 for the per-field vector segmentation compared to an overall accuracy of 56–60% and a κ coefficient of 0.37–0.42 for object-based approaches. Per-field vector segmentation was thus superior and used for LCLU classification at communal level. Overall accuracy scored 83% and the κ coefficient 0.7. In diversified agriculture, per-field vector segmentation and classification achieved higher classification results.  相似文献   

16.
A new approach for deformation monitoring of super high-rise building using GPS/BDS technology is proposed for the case when prior coordinates are known and the baseline is short but has a large height difference. The approach is based on the ambiguity function method (AFM). Considering that the double-differenced (DD) troposphere delay residual error cannot be ignored, the relative zenith tropospheric delay (RZTD) parameter is introduced into the original AFM equation. Thus, the RZTD and 3D coordinate parameters are together obtained through the modified AFM (MAFM). Due to the low computational efficiency of conventional AFM, an improved particle swarm optimization (IPSO) algorithm is used to search the four optimal parameters X/Y/Z/RZTD and replaces the grid search method. In this study, GPS/BDS deformation monitoring data for buildings with approximately 290 m height difference were used to verify the feasibility of the proposed MAFM. Numerical results show a single-epoch average computation time of approximately 0.3 s, which meets the requirements of near-real-time dynamic monitoring. The average accuracy of the GPS single-epoch RZTD solution is better than 1 cm, the combined GPS/BDS MAFM performance outperforms the GPS-only system, and using multi-epoch observations can further improve the accuracy of the RZTD solution. After RZTD correction, GPS/BDS monitoring precision can be improved, particularly the height dimension, whose precision is improved by approximately 6 cm.  相似文献   

17.
Changes in forest composition impact ecological services, and are considered important factors driving global climate change. A hybrid sampling method along with a modelling approach to map current and past land cover in Kunming, China is reported. MODIS land cover (2001–2011) data-sets were used to detect pixels with no apparent change. Around 3000 ‘no change points’ were systematically selected and sampled using Google Earth’s high-resolution imagery. Thirty-five per cent of these points were verified and used for training and validation. We used Random forests to classify multi-temporal Landsat imagery. Results show that forest cover has had a net decrease of 14385?ha (1.3% of forest area), which was primary converted to shrublands (11%), urban and barren land (2.7%) and agriculture (2.5%). Our validation indicates an overall accuracy (Kappa) of 82%. Our methodology can be used to consistently map the dynamics of land cover change in similar areas with minimum costs.  相似文献   

18.
In this study, we create and critically analyse an automated decision tree classification approach for regional level land cover mapping in insular South-East Asian conditions, using a combination of 10–30 m resolution optical and radar data. The resulting map contains 11 land cover classes and reveals a great deal of contextual information due to high spatial resolution. A limited accuracy assessment indicates 59–97% class wise accuracies. The unprecedented spatial detail of closed canopy oil palm mapping (with user’s accuracy of 90%) is seen as the most promising feature of the mapping approach. The incapability of separating primary forests from other tree cover, and the large variety of different landscapes (e.g. home gardens and tea plantations) classified as shrubland, are considered the main areas for future improvement. Overall, the study demonstrates the great potential of multi-source 10–30 m resolution high data volume land cover mapping approaches in insular South-East Asian conditions.  相似文献   

19.
North Maidan consist of seven districts of North Karnataka. It is named after its relatively low and subdued relief or landscape of monoto-nous plateau. Most of the area lies in the rain shadow of the Western Ghats. The land utilization map shows majority of the area during December and January months is under agriculture with fallow land as the second largest category Large areas of North Maidan are under grassland which look barren by the beginning of summer. A total of nine landuse categories were delineated wifh the help of Landsat data.  相似文献   

20.
This paper presents a new approach to improving land use/cover mapping accuracy in an urban environment. Bi-temporal Landsat TM images (1987 and 1997) were initially classified using the ISODATA method. An NDVI difference image was derived and classified, with each class indicating certain land use/cover changes. Temporal logical reasoning was then performed on the classified NDVI difference map and the initial land use/cover maps. The procedure successfully resolved the confusion between forest clear-cuts/fallow cropland and urban, as well as between forest clear-cuts and cropland. The kappa analysis test led to a Z value of 1.837 with the p-value of 0.026 for the year 1987, and a Z value of 1.924 with the p-value of 0.014 for 1997, indicating significant enhancement at the 95% confidence level.  相似文献   

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