scholarly journals Automatic Extraction of Water Inundation Areas Using Sentinel-1 Data for Large Plain Areas

2020 ◽  
Vol 12 (2) ◽  
pp. 243 ◽  
Author(s):  
Shunshi Hu ◽  
Jianxin Qin ◽  
Jinchang Ren ◽  
Huimin Zhao ◽  
Jie Ren ◽  
...  
Keyword(s):  
Active Contour Model ◽  
Kappa Coefficient ◽  
Morphological Operations ◽  
Initial Water ◽  
Entire Study ◽  
Water Classification ◽  
Sar Data ◽  
Entire Study Area ◽  
Water Inundation ◽  
Sentinel 2

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with the support of auxiliary datasets, using thresholding methods and followed by morphological operations to further refine the results. However, auxiliary datasets may lose efficacy on large plain areas, whilst the parameters of morphological operations are hard to be decided in different situations. Here, a heuristic and automatic water extraction (HAWE) method is proposed to extract the water map from Sentinel-1 SAR data. In the HAWE, we integrate tile-based thresholding and the active contour model, in which the former provides a convincing initial water map used as a heuristic input, and the latter refines the initial map by using image gradient information. The proposed approach was tested on the Dongting Lake plain (China) by comparing the extracted water map with the reference data derived from the Sentinel-2 dataset. For the two selected test sites, the overall accuracy of water classification is between 94.90% and 97.21% whilst the Kappa coefficient is within the range of 0.89 and 0.94. For the entire study area, the overall accuracy is between 94.32% and 96.7% and the Kappa coefficient ranges from 0.80 to 0.90. The results show that the proposed method is capable of extracting water inundations with satisfying accuracy.

Zwischenevaluation des Wald-Wild-Management-Instruments (WWMI) im Pilotprogramm effor2 «Wald und Wild» | Preliminary evaluation of the Game-Forest-Management-Tool (GFMT) in the effor2 pilot programme «Game and Forest»

2003 ◽  
Vol 154 (8) ◽  
pp. 305-313 ◽  
Author(s):  
Roman Eyholzer ◽  
Martin Baumann ◽  
Rolf Manser
Keyword(s):  
Forest Management ◽  
Management Practice ◽  
Management Tool ◽  
Preliminary Evaluation ◽  
Optimal Contract ◽  
Technical Tool ◽  
Entire Study ◽  
Pilot Programme ◽  
Complex Problems ◽  
Entire Study Area

Faced with the challenging task of balancing forest interests and wildlife, the Swiss Forest Agency initiated the pilot programme«Game and Forest», which is committed to a philosophy of goal-oriented management practice and a redesign of forestry subsidizing. Within this programme the diverse goals of forestry and hunting have been amalgamated to a superimposed goal and set out in a corresponding contract. The Game-Forest-Management-Tool (GFMT) has been divised to simulate the effect of various strategies to deal with the complex problems of forest-wildlife. Optimal contract-fulfilling procedures can be simulated on a PC using this technical tool. The efficiency of the measures suggested by simulations that were carried out are being tested in a study area within the pilot programme, «Game and Forest». Half way through this trial, after two years, we can say that there has been no significant increase of non-browsed areas. In 2004, after the collection of data for the entire study area, we will be able to tell whether applying this computer simulated strategy truly leads to an augmentation of non-browsed area and a decrease in bark-peeled forests in the pilot area.

scholarly journals Night-Time Light Remote Sensing Mapping: Construction and Analysis of Ethnic Minority Development Index

2021 ◽  
Vol 13 (11) ◽  
pp. 2129
Author(s):  
Fei Zhao ◽  
Lu Song ◽  
Zhiyan Peng ◽  
Jianqin Yang ◽  
Guize Luan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Ethnic Group ◽  
Ethnic Groups ◽  
Ethnic Minorities ◽  
Population Data ◽  
Night Time ◽  
Entire Study ◽  
Development Index ◽  
Remote Sensing Mapping ◽  
Entire Study Area

Using toponym data, population data, and night-time light data, we visualized the development index of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups on ArcGIS as well as the distribution of 25 ethnic minorities in the study area. First, we extracted the toponym data of 25 ethnic minorities in the study area, combined with night-time light data and the population proportion data of each ethnic group, then we obtained the development index of each ethnic group in the study area. We compared the development indexes of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups with higher development indexes. The results show that the Yi nationality’s development index was the highest, reaching 28.86 (with two decimal places), and the Dai nationality’s development index was the lowest (15.22). The areas with the highest minority development index were concentrated in the core area of the minority development, and the size varied with the minority’s distance. According to the distribution of ethnic minorities, we found that the Yi ethnic group was distributed in almost the entire study area, while other ethnic minorities had obvious geographical distribution characteristics, and there were multiple ethnic minorities living together. This research is of great significance to the cultural protection of ethnic minorities, the development of ethnic minorities, and the remote sensing mapping of lights at night.

scholarly journals Monitoring and simulating the distribution of phytoplankton in constructed wetlands based on SPOT 6 images

2021 ◽  
Vol 13 (1) ◽  
pp. 454-468
Author(s):  
Yumeng Song ◽  
Jing Zhang
Keyword(s):  
Water Quality ◽  
Water Quality Model ◽  
Quality Model ◽  
Band Ratio ◽  
Entire Study ◽  
Chl A ◽  
Analytical Tools ◽  
Best Fit ◽  
Entire Study Area ◽  
Range Of Values

Abstract We integrated hyperspectral and field-measured chlorophyll-a (Chl-a) data from the Kristalbad constructed wetland in the Netherlands. We developed a best-fit band ratio empirical algorithm to generate a distribution map of Chl-a concentration (C chla) from SPOT 6 imagery. The C chla retrieved from remote sensing was compared with a water quality model established for a wetland pond system. The retrieved satellite results were combined with a water quality model to simulate and predict the changes in phytoplankton levels. The regression model provides good retrievals for Chl-a. The imagery-derived C chla performed well in calibrating the simulation results. For each pond, the modeled C chla showed a range of values similar to the Chl-a data derived from SPOT 6 imagery (10–25 mg m−3). The imagery-derived and prediction model results could be used as the guiding analytical tools to provide information covering an entire study area and to inform policies.

scholarly journals Assessing the Natural Recovery of Mangroves after Human Disturbance Using Neural Network Classification and Sentinel-2 Imagery in Wunbaik Mangrove Forest, Myanmar

2020 ◽  
Vol 13 (1) ◽  
pp. 52
Author(s):  
Win Sithu Maung ◽  
Jun Sasaki
Keyword(s):  
Neural Network ◽  
Change Detection ◽  
Transfer Learning ◽  
Mangrove Forest ◽  
Kappa Coefficient ◽  
Mangrove Forests ◽  
Ann Model ◽  
Shrimp Ponds ◽  
Natural Recovery ◽  
Sentinel 2

In this study, we examined the natural recovery of mangroves in abandoned shrimp ponds located in the Wunbaik Mangrove Forest (WMF) in Myanmar using artificial neural network (ANN) classification and a change detection approach with Sentinel-2 satellite images. In 2020, we conducted various experiments related to mangrove classification by tuning input features and hyper-parameters. The selected ANN model was used with a transfer learning approach to predict the mangrove distribution in 2015. Changes were detected using classification results from 2015 and 2020. Naturally recovering mangroves were identified by extracting the change detection results of three abandoned shrimp ponds selected during field investigation. The proposed method yielded an overall accuracy of 95.98%, a kappa coefficient of 0.92, mangrove and non-mangrove precisions of 0.95 and 0.98, respectively, recalls of 0.96, and F1 scores of 0.96 for the 2020 classification. For the 2015 prediction, transfer learning improved model performance, resulting in an overall accuracy of 97.20%, a kappa coefficient of 0.94, mangrove and non-mangrove precisions of 0.98 and 0.96, respectively, recalls of 0.98 and 0.97, and F1 scores of 0.96. The change detection results showed that mangrove forests in the WMF slightly decreased between 2015 and 2020. Naturally recovering mangroves were detected at approximately 50% of each abandoned site within a short abandonment period. This study demonstrates that the ANN method using Sentinel-2 imagery and topographic and canopy height data can produce reliable results for mangrove classification. The natural recovery of mangroves presents a valuable opportunity for mangrove rehabilitation at human-disturbed sites in the WMF.

PREDATION BY CALOSOMA SYCOPHANTA L. (COLEOPTERA: CARABIDAE): EVIDENCE FOR A LARGE IMPACT ON GYPSY MOTH, LYMANTRIA DISPAR L. (LEPIDOPTERA: LYMANTRIIDAE), PUPAE

1985 ◽  
Vol 117 (9) ◽  
pp. 1117-1126 ◽  
Author(s):  
Ronald M. Weseloh
Keyword(s):  
Gypsy Moth ◽  
Lymantria Dispar ◽  
Ground Level ◽  
Mortality Factor ◽  
Substantial Impact ◽  
Entire Study ◽  
Dispersal Potential ◽  
Capture Recapture ◽  
The Impact ◽  
Entire Study Area

AbstractThe impact of predation by Calosoma sycophanta L. on an increasing prey population was assessed by recapturing marked adult beetles, periodically observing tagged gypsy moth pupae, and examining gypsy moth pupal remains in different microhabitats. Adult beetles dispersed in random directions but many tended to remain near the trap at which they were originally caught, suggesting a low dispersal potential. About 75% of the adult beetles present in the plot on one day were still present the next day. Capture–recapture estimates suggested that there were at most about 250 male beetles and half as many females/ha in the plot. Calosoma larvae destroyed 70% of tagged gypsy moth pupae under burlap bands on tree trunks near ground level, which was much more than any other mortality factor. Although this percentage was the same when mortality was assessed by looking at pupal remains within 5 m of the ground on tree trunks, pupae higher in trees and on leaves were not attacked as frequently. On average, about 40% of the pupae present in the entire study area were destroyed by Calosoma larvae. Each female beetle in the site would have had to produce about 30 progeny to have this effect. These data suggest that a relatively low number of adult beetles can have a substantial impact on gypsy moth populations.

scholarly journals DETERMINATION AND MAPPING OF THE TERRESTRIAL GRAVITY ANOMALIES IN THE MOUNTAINOUS AREAS OF IRAQ

2021 ◽  
Vol 6 (24) ◽  
pp. 213-225
Author(s):  
Shazad Jamal Jalal ◽  
Tajul Ariffin Musa ◽  
Ami Hassan Md Din ◽  
Wan Anom Wan Aris
Keyword(s):  
Gravity Data ◽  
Physical Geodesy ◽  
Gravity Anomalies ◽  
Gravity Survey ◽  
Mountainous Areas ◽  
Entire Study ◽  
Terrestrial Gravity ◽  
The Past ◽  
Regional Gravity ◽  
Entire Study Area

Gravity data and computing gravity anomalies are regarded as vital for both geophysics and physical geodesy fields. The mountainous areas of Iraq are characterized by the lack of regional gravity data because gravity surveys are rarely performed in the past four decades due to the Iraq-Iran war and the internal unstable political situation of this particular region. In addition, the formal map of the available terrestrial gravity which was published by the French Database of Bureau Gravimetrique International (International Gravimetric Bureau-in English) (BGI), introduces Iraq and the study area as a remote area and in white color because of the unavailability of gravity data. However, a dense and local (not regional) gravity data is available which was conducted by geophysics researchers 13 years ago. Therefore, the regional gravity survey of 160 gravity points was performed by the authors at an average 11 km apart, which was covers the whole area of Sulaymaniyah Governorate (part of the mountainous areas of Iraq). In spite of Although the risk of mine fields within the study area, suitable safe routes as well as a helicopter was used for the gravity survey of several points on the top of mountains. The survey was conducted via Lacoste and Romberg geodetic gravimeter and GPS handheld. The objective of the study is to determine and map the gravity anomalies for the entire study area, the data of which would assist different geosciences applications.

scholarly journals GIS based Soil Nutrient Assessment of Available Macro and Micronutrients in Tommaladahalli Microwatershed of Chikkamagaluru District, Karnataka, India

2021 ◽  
Vol 10 (9) ◽  
pp. 510-517
Author(s):  
S. Anitha ◽  
K. T. Gurumurthy Ganapathi
Keyword(s):  
Interpolation Method ◽  
Soil Nutrient ◽  
Nutrient Status ◽  
Nitrogen And Phosphorus ◽  
Available Nitrogen ◽  
Entire Study ◽  
Available N ◽  
Standard Procedures ◽  
Entire Study Area ◽  
Available Nutrient Status

An investigation was undertaken in Tommaladahalli (566.13 ha) micro-watershed of Tarikere taluk, Chikkamagaluru district of Karnataka to assess available nutrient status in the surface soils. About 118 surface soil samples were collected grid wise by using cadastral map at 250 m grid interval and were analyzed for their fertility status using standard procedures. Soil fertility maps were prepared by means of interpolation method called Krigging. The results revealed that the pH, electrical conductivity, and organic carbon were ranged from 5.37 to 9.06, 0.065 to 0.466 dS m-1 and 0.33 to 1.62 per cent respectively. The available N, P2O5, K2O were ranged from 175.6 to 545.6 kg ha-1, 11.8 to 61.1 kg ha-1 and 122.7 to 491.4 kg ha-1, respectively. The available nitrogen and phosphorus were low to medium, where as potassium content was medium to high in the entire study area. Micronutrients viz. zinc, iron and boron were sufficient and were ranged from 0.34 to 1.17 mg kg-1, 2.03 to 21.86 mg kg-1 and 0.30 to 0.89 mg kg-1 respectively.

scholarly journals An Approach for Downscaling SMAP Soil Moisture by Combining Sentinel-1 SAR and MODIS Data

2019 ◽  
Vol 11 (23) ◽  
pp. 2736 ◽  
Author(s):  
Jueying Bai ◽  
Qian Cui ◽  
Wen Zhang ◽  
Lingkui Meng
Keyword(s):  
Soil Moisture ◽  
Vegetation Cover ◽  
Land Surface ◽  
Feature Space ◽  
Entire Study ◽  
Vegetation Indexes ◽  
Input Variables ◽  
Entire Study Area ◽  
Infrared Data

A method is proposed for the production of downscaled soil moisture active passive (SMAP) soil moisture (SM) data by combining optical/infrared data with synthetic aperture radar (SAR) data based on the random forest (RF) model. The method leverages the sensitivity of active microwaves to surface SM and the triangle/trapezium feature space among vegetation indexes (VIs), land surface temperature (LST), and SM. First, five RF architectures (RF1–RF5) were trained and tested at 9 km. Second, a comparison was performed for RF1–RF5, and were evaluated against in situ SM measurements. Third, two SMAP-Sentinel active–passive SM products were compared at 3 km and 1 km using in situ SM measurements. Fourth, the RF5 model simulations were compared with the SMAP L2_SM_SP product based on the optional algorithm at 3 km and 1 km resolutions. The results showed that the downscaled SM based on the synergistic use of optical/infrared data and the backscatter at vertical–vertical (VV) polarization was feasible in semi-arid areas with relatively low vegetation cover. The RF5 model with backscatter and more parameters from optical/infrared data performed best among the five RF models and was satisfactory at both 3 km and 1 km. Compared with L2_SM_SP, RF5 was more superior at 1 km. The input variables in decreasing order of importance were backscatter, LST, VIs, and topographic factors over the entire study area. The low vegetation cover conditions probably amplified the importance of the backscatter and LST. A sufficient number of VIs can enhance the adaptability of RF models to different vegetation conditions.

scholarly journals Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China

2020 ◽  
Vol 12 (21) ◽  
pp. 3539
Author(s):  
Haifeng Tian ◽  
Jie Pei ◽  
Jianxi Huang ◽  
Xuecao Li ◽  
Jian Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Winter Wheat ◽  
Satellite Imagery ◽  
Remote Sensing Data ◽  
Northern China ◽  
Google Earth ◽  
Kappa Coefficient ◽  
Landsat 8 ◽  
Winter Crops ◽  
Sentinel 2

Garlic and winter wheat are major economic and grain crops in China, and their boundaries have increased substantially in recent decades. Updated and accurate garlic and winter wheat maps are critical for assessing their impacts on society and the environment. Remote sensing imagery can be used to monitor spatial and temporal changes in croplands such as winter wheat and maize. However, to our knowledge, few studies are focusing on garlic area mapping. Here, we proposed a method for coupling active and passive satellite imagery for the identification of both garlic and winter wheat in Northern China. First, we used passive satellite imagery (Sentinel-2 and Landsat-8 images) to extract winter crops (garlic and winter wheat) with high accuracy. Second, we applied active satellite imagery (Sentinel-1 images) to distinguish garlic from winter wheat. Third, we generated a map of the garlic and winter wheat by coupling the above two classification results. For the evaluation of classification, the overall accuracy was 95.97%, with a kappa coefficient of 0.94 by eighteen validation quadrats (3 km by 3 km). The user’s and producer’s accuracies of garlic are 95.83% and 95.85%, respectively; and for the winter wheat, these two accuracies are 97.20% and 97.45%, respectively. This study provides a practical exploration of targeted crop identification in mixed planting areas using multisource remote sensing data.

Study on Influence Law of Urban Architectural Structure on the Automobile Exhaust Diffusion Based on CFD

2012 ◽  
Vol 178-181 ◽  
pp. 751-755
Author(s):  
Yong Zhang ◽  
Zheng Qi Gu ◽  
Zhen Wang ◽  
Yong Yu
Keyword(s):  
Wind Direction ◽  
Volume Fraction ◽  
Great Influence ◽  
Entire Study ◽  
Automobile Exhaust ◽  
Average Value ◽  
Near Earth Space ◽  
Urban Buildings ◽  
Structural Layout ◽  
Entire Study Area

For study the law of urban buildings, in particular, the buildings at both roads’ sides in crossroads impacting on the diffusion of automobile exhaust, using CFD, combined with meteorological wind，simulates a crossroads automobile exhaust diffusion processing during waiting 35s. The results are following: in poor circulation areas, CO volume fraction in the buildings near-Earth space is up to 1.0e-7 and more than 100 times average value of the entire study area, so buildings structural layout has great influence. After Analysis, propose that local meteorological wind direction and speed should be considered and different height gradient design should be selected in buildings structural layout, so that the exhaust spread rapidly and drift to the urban high altitude, in order to improve air quality.

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