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# Analysis of the MNDWI Index of Gravel Mines Around the South Platte River Using Landsat Satellite Images
(1982–2024)

Rey Louis, Hervé Piegay, Lise Vaudor

► To cite this version:

Rey Louis, Hervé Piegay, Lise Vaudor. Analysis of the MNDWI Index of Gravel Mines Around the South Platte River Using Landsat Satellite Images (1982–2024). 2024. hal-04923875v2

HAL Id: hal-04923875

https://hal.science/hal-04923875v2

Preprint submitted on 19 Feb 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# Analyze of index
MNDWI of gravels
mines around
South Platte River
from Landsat
satellites images
from 1982 to 2024
# Contents

<table><tr><td>1</td><td>Introduction</td><td>2</td></tr><tr><td>2</td><td>Materiel and method</td><td>3</td></tr><tr><td>2.1</td><td>Extract indexes from landsat images</td><td>3</td></tr><tr><td>2.2</td><td>Plot data</td><td>3</td></tr><tr><td>2.3</td><td>Add the slopes of changes in the MNDWI index evolution</td><td>3</td></tr><tr><td>2.4</td><td>Extract in a table the year of changes of slope</td><td>3</td></tr><tr><td>2.4.1</td><td>Pieces of South Platte River in the area of reservoirs</td><td>3</td></tr><tr><td>2.4.2</td><td>Reservoirs</td><td>Error! Bookmark not defined.</td></tr><tr><td>2.5</td><td>Mapp the year of appearance of water in the reservoirs</td><td>4</td></tr><tr><td>3</td><td>Résults</td><td>5</td></tr><tr><td>3.1</td><td>Plot for each portion of river the MNDWI index</td><td>5</td></tr><tr><td>3.2</td><td>Plot for each reservoir the MNDWI index</td><td>Error! Bookmark not defined.</td></tr><tr><td>3.2.1</td><td>Plot graphs of all reservoirs with a pen.value of 50 and map the year of plenty water appearance</td><td>5</td></tr><tr><td>3.2.2</td><td>Plot reservoirs with a pen.value changed to 25 and 5</td><td>11</td></tr><tr><td>4</td><td>Bibliography</td><td>12</td></tr></table>
# 1 Introduction

The area of study is in the North of the City Denver in Colorado state in USA (Figure 1).

According to the last update of Google earth, we drew by hands the limits of reservoirs. Actually all reservoirs could have been full of partly in water through years. We tried to include the major part of old mine transformed in reservoir along South Platte river from the portion Denver to the south of Platteville.

If the reservoir width is smaller than 30 meters we did not include it because the Landsat images used have a spatial resolution of 30 meters.

We used the algorithm PELT to determine the changes of slopes with manual pen.value. The pen.value is sometimes different for some plot as you will see below. I stratified from pen.value = 50 meaning a low sensitivity of change. That's why when there is high variability I used lower pen.avlue.

In total there are 173 objects : 170 reservoirs and 3 pieces of active channel of the river.

The aims of the project are : (1) to follow the variations of water presence in the reservoirs and also in the river through MNDWI index extracted from Landsat data series. Through these observations, we will be able to know the date when the water appeared in the reservoir and when it disappeared. (2) Create a map showing the spatiality of the appearance of water in reservoirs through a range of years.

<figure><img src="image_3.png" /><figcaption>Figure 1 : Area of study</figcaption></figure>
# 2 Materiel and method

## 2.1 Extract indexes from Landsat images

At laboratory EVS we used the Google Earth Engine plateform to applied a script made internally at the laboratory EVS at Lyon to extract metrics from Landsat images from 1982 to january 2024.

This code extract a lot of informations and spectrals indexes. Here we only look at the MNDWI index.

The index MNDWI is The Modified Normalized Difference Water Index.

$$MNDWI = (Green band - SWIR band) / (Green band + SWIR band)$$

The Landsat images have 7 or 8 bands and they all have the bands Green and the band SWIR.

Bands used in Landsat :

* Green band → Band 2 : 0.52-0.6 micrometers

* SWIR 1 band → Band 5 : 1.55-1.75 micrometers

This two bands have 30 meters in spatiale resoluton (look at the link to learn more : https://www.usgs.gov/faqs/what-are-band-designations-landsat-satellites)

## 2.2 Plot data

We plotted in x axis the time from the Landsat images that are available from 1982 to 2023 and in y axis the mean of all pixel of MNDWI index in a whole polgon of reservoir. Before that we removed the outliers through Interquartile Range to Detect (IQR).

## 2.3 Add the slopes of changes in the MNDWI index evolution

In order to know when there a change or several changes of slope(s) in the MNDWI index we used this alogorithm PELT evelopped by Lise Vaudor (https://perso.ens-lyon.fr/lise.vaudor/detection-automatique-de-ruptures-dans-un-signal-package-changepoint/) which is based on the package R changepoint de Killick and Eckley (2011, https://cran.r-project.org/web/packages/changepoint/index.html).

In the algorithme PELT there is value of penalty which could changed according to the variability of your data from the mean or variance. To start we used pen.value = 50. For the most of value of polygons this value worked well.

## 2.4 Extract in a table the year of changes of slope

### 2.4.1 Pieces of South Platte River in the area of reservoirs

The segments of the South Platte River have been delineated both upstream (Polygon 0), in the middle section of the studied river stretcha and with the final segment identified at the end of the study area. The delineated polygons encompass the riverbanks, as well as sections of gravel and water from the active channel.
## 2.5 Mapp the year of appearance of water in the reservoirs

We extracted the date when water became visible (MNDWI around 0). To determine the date of water appearance, we retained the date where there is a change in slope and when the value of MNDWI is within the range of [-0.08; +0.08]. During observations of the polygon boundaries, there are occasionally areas that likely consist of solid ground. These ground sections may significantly influence factors such as water turbidity, affecting the reflectance of bands and consequently, the MNDWI index. That's why we chose to use a range of MNDWI index.

The aim here is to show the evolution of water appearance for all reservoirs through periods defined.
# 3 Résults

## 3.1 Plot for each portion of river the MNDWI index

For the portion of river we used a pen.value according to the sensibility we needed to see the breakups

As we can see in the figures the first piece of the river (number 0, close to Commerce City at the North of Denver) as a mean MNDWI without notable change of slope with a value around -0.12. However the second one (number 1, close to Brighton) has known two importantes breakups (19/08/1999 and 8/11/2017) of slope, moving a little further away from the value 0 value each time, meaning there less and less water surface. For the third one (number 2, in the North of Fort Lupton), there is one change (28/02/2018) of slope indicates a decreasing of water surface as well.

For the majority of reservoirs the pen.value = 50 fit well the changes of slopes.

However for some of them we needed to increase the sensibility of the PELT algorithm in decreasing the pen.value at 25 (polygons : 26,51,78103,125,141) and 5 (polygons : 44,55,73,122,136)

### 3.1.1 Plot graphs of all reservoirs with a pen.value of 50 and map the year of plenty water appearance

We plot 20 polygons by 20 polygons to get a clear sight of the terrain. Firstly we used a pen.value of 50 for the PELT algorithm. We applied a range of appearance of entirely water in reservoir of nine periods of years.

<figure><img src="image_4.png" /></figure>
Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40

<figure><img src="image_5.png" /></figure>

Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60

<figure><img src="image_6.png" /></figure>
Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80

<figure><img src="image_7.png" /></figure>
Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100

<figure><img src="image_8.png" /></figure>

Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100

<figure><img src="image_9.png" /></figure>
Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120

<figure><img src="image_10.png" /></figure>

Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50
Polygon: 161,162,163,164,165,166,167,168,169,170,171

<figure><img src="image_11.png" /></figure>
Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50

Polygon : 121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140

<figure><img src="image_12.png" /></figure>

Evolution index Mean MNDWI for each reservoir and slope identified by PELT method with pen.value = 50

Polygon : 141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160

<figure><img src="image_13.png" /></figure>
3.1.2 Plot reservoirs with a pen.value changed to 25 and 5

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>
<figure><img src="image_16.png" /><figcaption>4 Mapping the threshold for mining appearance</figcaption></figure>
<figure><img src="image_17.png" /></figure>

References: Landsat images, january 2024.
Map made by L.Rey (march, 2024)

<figure><img src="image_18.png" /></figure>

References: Landsat images, january 2024.
Map made by L.Rey (march, 2024)
<figure><img src="image_19.png" /></figure>

References: Landsat images, January 2024.

Map made by L.Rey (march, 2024)

<figure><img src="image_20.png" /></figure>

References: Landsat images, January 2024.

Map made by L.Rey (march, 2024)
<figure><img src="image_21.png" /></figure>

References: Landsat images, january 2024.

Map made by L.Rey (march, 2024)

<figure><img src="image_22.png" /></figure>

References: Landsat images, january 2024.

Map made by L.Rey (march, 2024)
<figure><img src="image_23.png" /></figure>