Evidence map›Paper›PMID 36156949›Full record

ArticleComputational intelligence and neuroscience2022

Sponge City Planning and Information System Development Based on Geographic Information Fuzzy Processing.

Mingxin Gan, Tongfang Li

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mingxin GanUniversity of Science and Technology Beijing, Beijing 100083, China.ORCID https://orcid.org/0000-0002-0267-432X
Tongfang LiUniversity of Science and Technology Beijing, Beijing 100083, China.ORCID https://orcid.org/0000-0002-4979-3940

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the development of the urban water system from 1.0 to 3.0, the impervious surface area gradually increased, hindering the natural infiltration and self-purification process of urban rainwater, resulting in serious urban water pollution, urban waterlogging in the rainy season, and groundwater problems. Since water will seep into the ground, serious water pollution will cause damage to the ground. Therefore, in dealing with urban rainwater problems, we want to use the sponge's ability to absorb and store water to build our cities into sponge cities. In this paper, we have constructed a sponge city planning and information system development based on geographic information fuzzy processing. We use differentiated fuzzy processing methods to eliminate classified information to achieve a perfect combination with nearby images and use ordinary fuzzy processing methods to solve the problem of nonconfidential information. This paper discusses the impact of natural topography on the planning and construction of sponge cities, including whether natural topography will affect rainwater, whether it will affect the distribution of different strata, and whether it will affect the utilization of groundwater resources. The basic functions of this platform are provided by a series of functions of GIS, and multiple modules are developed according to management requirements. The initial state of street view data is a lot of fisheye lens photos and corresponding point location information, which are displayed online after data preprocessing, detection information, editing information, and blurring processing.

Indexed as

City PlanningRainChinaCitiesInformation SystemsWaterWater

Identifiers

PMID36156949
PMCPMC9499764

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.