Monitoring of current land use pattern of Ramsar designated Kolleru Wetland, India using geospatial technologies

Shivakrishna, Avadootha; Ramteke, Karankumar; Kesavan, S.; Prasad, Pankaj; Naidu, B.C.; Dhanya, M. B.; Abidi, Zeba Jaffer

doi:10.22438/jeb/42/1/mrn-1404

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…This energy is composed of many forms, among which electromagnetic wave is the earliest energy recognized and utilized by human beings. The monitoring methods of RS technology for forest ecosystem restoration can be summarized into two types [11]: one is to compare the changes of land use area/type at different times after classifying RS data at different times; The other is to judge by calculating the correlation index that reflects the change of forest vegetation. RS dynamic monitoring of mine geological environment refers to the monitoring of mine geological environment through natural electromagnetic energy such as light, heat and wireless waves during the monitoring process.…”

Section: Application Of Rs In Mine Ecological Restorationmentioning

confidence: 99%

Application of Remote Sensing Technology in Mine Ecological Restoration

2023

AJEE

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In the important stage of ecological civilization construction, the ecological restoration of abandoned mines is imminent. Mine geological environment monitoring is the premise of developing mine production, and only comprehensive geological environment data can provide guarantee for mine production. Conventional land resources survey methods have relatively long data cycle and poor accuracy, and can not provide timely, accurate and all-round information. Before the mine ecological restoration, it is necessary to investigate the mine ecological environment, mainly the land use, soil erosion and vegetation coverage of the mine. The application of remote sensing (RS) technology in land survey and dynamic monitoring can grasp the specific situation of land resources in real time, lay a good foundation for land survey and management, and further ensure the timeliness and rationality of land resources. This aricle studies the application of surveying and mapping technology in RS dynamic monitoring of mine geological environment, in order to improve the real-time monitoring of mine, so as to make accurate prediction and minimize the economic losses and casualties in mining areas.

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Section: Application Of Rs In Mine Ecological Restorationmentioning

confidence: 99%

Application of Remote Sensing Technology in Mine Ecological Restoration

2023

AJEE

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“…To better manage land use by discerning human interactions with natural phenomena, timely and accurate change detection needs to be employed. Among changes, the trend of land-use change caused by humans is regarded as one of the most significant factors affecting global changes in the environment [5]. Timely and accurate change detection of Earth's surface features provides a basis for a better understanding of the interactions between human and natural phenomena to better manage land cover.…”

Section: Introductionmentioning

confidence: 99%

Development of LR-PCA Based Fusion Approach to Detect the Changes in Mango Fruit Crop by Using Landsat 8 OLI Images

et al. 2022

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Change detection (CD) is the process of detecting changes from multi-temporal satellite images that have undergone spatial changes due to natural phenomena and/or human-induced activities. Mango is a major fruit crop in India, but detection of changes in mango crops remains a challenging task because the reason that many perennial crops have similar reflectance profiles. Therefore, a potent change detection technique is required for different applications such as the rate of deforestation, urban developments, damage evaluation, and resource monitoring. Compared to annual and seasonal crops, relatively few studies have been conducted on change detection in perennial fruit crops. In this study, a novel change detection technique (i.e., LR-PCA) is developed using the fusion of log-ratio (LR) and principal component analysis (PCA) images derived from bi-temporal soil adjusted vegetation index (SAVI) images to extract meaningful information and detect temporal changes in the mango fruit crop areas with high change detection accuracy. The proposed approach comprised two steps: (1) SAVI images from 2015 and 2019 were used to retrieve the log-ratio (LR) and principal component (PC) images, respectively, and both the images were fused by applying the pixel-by-pixel fusion approach. (2) Fused images were classified into three classes: "positive change", "no change", and "negative change" using a derived threshold value. The results show that the LR-PCA method of change detection yields a high change detection accuracy of 92% in comparison with the other change detection methods viz. vegetation image differencing, image ratioing, PCA, and log-ratio. To validate the adaptability of the proposed algorithm, experiments with two sets of bi-temporal SAVI indices images belonging to the Sitapur district of Uttar Pradesh State determine that the proposed change detection method performs well as compared to the existing individual methods for detection of changes in mango fruit crop. The proposed method is expected to be useful for detecting changes in the area of perennial crops. In the future, an accurate and efficient change detection analysis may be helpful for developing a real-time mango fruit crop monitoring system at the national level.INDEX TERMS Landsat 8 OLI, change detection, log ratio, principal component analysis, mango crop.

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