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Titlebook: Geo-Environmental Hazards using AI-enabled Geospatial Techniques and Earth Observation Systems; Tanupriya Choudhury,Bappaditya Koley,Atul

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51#
發(fā)表于 2025-3-30 11:19:35 | 只看該作者
GIS Mapping and Groundwater Quality Assessment Near Solid Waste Dump Site,water is required. The primary goal of the current study is to evaluate the quality of the groundwater near the Uruli Devachi solid waste disposal site in Pune, Maharashtra. In 2014, pre-monsoon and post-monsoon water samples were taken, and basic impurities such as pH, turbidity, sodium, and magnes
52#
發(fā)表于 2025-3-30 14:20:46 | 只看該作者
Assessment of Groundwater Potential Using an Integrated Approach of GIS, Fuzzy AHP, and Remote Sensf each thematic layer were given using FAHP. The final results of potential groundwater zones were grouped into very poor, poor, moderate, good, and very good. The parameters of slope, land use/land cover, geology, drainage density, and geomorphology have greater importance in storing more groundwat
53#
發(fā)表于 2025-3-30 19:31:27 | 只看該作者
Developing Sustainable Livelihood Index for the Coastal Belt of Indian Sundarbans,e of the coastal belt of Indian Sundarbans, based on the primary survey of 750 households from three coastal parts of Indian Sundarbans—Basanti, Gosaba, and Namkhana. Our SLI is built up based on eight subindices, each of which is developed based on certain variables or attributes whose total number
54#
發(fā)表于 2025-3-30 22:28:12 | 只看該作者
Computer Vision-Based Autonomous Underwater Vehicle with Robotic Arm for Garbage Detection and Cleaacy in object detection and classification of five garbage categories. The system incorporates a dataset of 1200 annotated images, which is further augmented to 1:8 proportion for model development. Overall, this integrated architecture enables efficient underwater garbage detection, collection, and
55#
發(fā)表于 2025-3-31 04:07:25 | 只看該作者
GIS and Remote Sensing Application for Vegetation Mapping,
56#
發(fā)表于 2025-3-31 05:04:48 | 只看該作者
57#
發(fā)表于 2025-3-31 11:27:27 | 只看該作者
58#
發(fā)表于 2025-3-31 15:57:54 | 只看該作者
59#
發(fā)表于 2025-3-31 18:30:25 | 只看該作者
60#
發(fā)表于 2025-4-1 00:50:24 | 只看該作者
https://doi.org/10.1007/978-3-322-88418-3, Philippines. Results showed that elevation, soil texture, drainage density, slope, and annual rainfall are the main predictors of flooding in the province. Also, approximately 4512 hectares in Marinduque were under moderate to very high flooding hazards.
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