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Merge pull request 'master' (#15) from jits/FarmMapsApiClient_WURtest:master into master

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Reviewed-on: FarmMaps/FarmMapsApiClient#15
This commit is contained in:
Mark van der Wal 2023-11-02 11:01:02 +00:00
commit bb4e795abc
9 changed files with 564 additions and 494 deletions
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2
FarmmapsApi/Constants.cs
View File

@ -19,7 +19,7 @@ namespace FarmmapsApiSamples
public const string VRAHAULMKILLING_TASK = "vnd.farmmaps.task.vrahaulmkilling";
public const string VRAPLANTING_TASK = "vnd.farmmaps.task.vrapoten";
public const string VRAZONERING_TASK = "vnd.farmmaps.task.vrazonering";
public const string SATELLITE_TASK = "vnd.farmmaps.task.sentinelhub";
public const string SATELLITE_TASK = "vnd.farmmaps.task.sentinelhub"; //"vnd.farmmaps.task.satellite";
public const string VANDERSAT_TASK = "vnd.farmmaps.task.vandersat";
public const string TASKMAP_TASK = "vnd.farmmaps.task.taskmap";
public const string WORKFLOW_TASK = "vnd.farmmaps.task.workflow";

165
FarmmapsBulkSatDownload/BulkSatDownloadApplication.cs
View File

@ -25,6 +25,7 @@ namespace FarmmapsBulkSatDownload
private readonly GeneralService _generalService;
public const string settingsfile = "Settings.json";
public const int firstAvailableYear = 2017;
private Settings _settings;
public BulkSatDownloadApplication(ILogger<BulkSatDownloadApplication> logger, FarmmapsApiService farmmapsApiService,
@ -51,6 +52,13 @@ namespace FarmmapsBulkSatDownload
DateTime lastdownloadedimagedate;
int cropYear;
//Use doDB to decide if reading from/writing to database (doDB = true) or
//read from file BulkSatDownloadInput.json and write satellite statistics to file(s) specified in BulkSatDownloadInput.json
//note in case of doDB == true you will need to provide a file "DBsettings.secrets.json" with login details for the database
//see empty example "DBsettings.json"
bool doDB = false;
if (doDB == true)
{
// Option 1: When using database need to (1) fill in database data in DBsettings.secrets.json; (2) write tailor made SELECT query for fieldinputs in following lines;
// (3) Write tailor made INSERT INTO query in Task Process() below;
// Initialize databases. Username, password etc stored in file "DBsettings.secrets.json".
@ -74,16 +82,16 @@ namespace FarmmapsBulkSatDownload
List<string> satelliteBands = new List<string> { "wdvi", "ndvi" };
string connectionString = dbparcels.GetConnectionString();
string readSql = string.Format(
@"
SELECT pt.arbid, pt.year, gml.lastwenrdate, ST_AsGeoJSON(ST_Transform((ST_DUMP(pt.geom)).geom::geometry(Polygon),4326)) AS geojson_polygon_wgs84,
@"
SELECT pt.arbid, pt.year, gml.lastwenrdate, ST_AsGeoJSON(ST_Transform((ST_DUMP(pt.geom)).geom::geometry(Polygon),4326)) AS geojson_polygon_wgs84,
COALESCE(pt.cropfielditemcode,'') AS cropfielditemcode,
CASE WHEN pt.year >= DATE_PART('year', CURRENT_DATE) THEN '' ELSE COALESCE(pt.satellitetaskcode,'') END AS satellitetaskcode
FROM {0}.{1} pt, {0}.{2} gml
WHERE
FROM {0}.{1} pt, {0}.{2} gml
WHERE
pt.arbid = gml.arbid
AND pt.satellitetaskcode IS NULL
ORDER BY pt.arbid
LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x for testing
ORDER BY pt.arbid
LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x for testing
using (NpgsqlConnection connection = new NpgsqlConnection(connectionString))
{
@ -112,34 +120,35 @@ LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x
}
connection.Close();
}
// Now choose which list you want to use
bulkSatDownloadInputList = bulkSatDownloadInputListDB;
}
else
{
// Option 2: Example without database. Comment out this part if you want to use database
// Read cropfields "BulkSatDownloadInput.json" and write all stats to a single csv file
// Write all stats for multiple fields will be written to a single csv file
//string downloadFolder;
//string fileNameStats;
//string headerLineStats = $"FieldName,satelliteDate,satelliteBand,max,min,mean,mode,median,stddev,minPlus,curtosis,maxMinus,skewness,variance,populationCount,variationCoefficient,confidenceIntervalLow, confidenceIntervalHigh,confidenceIntervalErrorMargin" + Environment.NewLine;
//var fieldsInputJson = File.ReadAllText("BulkSatDownloadInput.json");
//bulkSatDownloadInputListCsv = JsonConvert.DeserializeObject<List<BulkSatDownloadInput>>(fieldsInputJson);
//for (int i = 0; i < bulkSatDownloadInputListCsv.Count; i++)
//{
// downloadFolder = bulkSatDownloadInputListCsv[i].downloadFolder;
// fileNameStats = Path.Combine(downloadFolder, bulkSatDownloadInputListCsv[i].fileNameStats);
// if (!Directory.Exists(downloadFolder))
// Directory.CreateDirectory(downloadFolder);
// bulkSatDownloadInputListCsv[i].fileNameStats = fileNameStats;
// // Header same as in GeneralService.DownloadSatelliteStats
// // Delete fileNameStats if existing. Create a new file. Add a header to csv file
// File.Delete(fileNameStats);
// File.AppendAllText(fileNameStats, headerLineStats);
//}
string downloadFolder;
string fileNameStats;
string headerLineStats = $"FieldName,satelliteDate,satelliteBand,max,min,mean,mode,median,stddev,minPlus,curtosis,maxMinus,skewness,variance,populationCount,variationCoefficient,confidenceIntervalLow, confidenceIntervalHigh,confidenceIntervalErrorMargin" + Environment.NewLine;
var fieldsInputJson = File.ReadAllText("BulkSatDownloadInput.json");
bulkSatDownloadInputListCsv = JsonConvert.DeserializeObject<List<BulkSatDownloadInput>>(fieldsInputJson);
for (int i = 0; i < bulkSatDownloadInputListCsv.Count; i++)
{
downloadFolder = bulkSatDownloadInputListCsv[i].downloadFolder;
fileNameStats = Path.Combine(downloadFolder, bulkSatDownloadInputListCsv[i].fileNameStats);
if (!Directory.Exists(downloadFolder))
Directory.CreateDirectory(downloadFolder);
bulkSatDownloadInputListCsv[i].fileNameStats = fileNameStats;
// Header same as in GeneralService.DownloadSatelliteStats
// Delete fileNameStats if existing. Create a new file. Add a header to csv file
File.Delete(fileNameStats);
File.AppendAllText(fileNameStats, headerLineStats);
}
// Now choose which list you want to use
bulkSatDownloadInputList = bulkSatDownloadInputListDB; //bulkSatDownloadInputListDB; //bulkSatDownloadInputListCsv;
// Whichever option (database or json/csv), continue here
// Delete the settingsfile
// File.Delete(settingsfile);
bulkSatDownloadInputList = bulkSatDownloadInputListCsv;
}
// For each input download all images. Keep track to time, important when doing bulk downloads
var watch = System.Diagnostics.Stopwatch.StartNew();
@ -191,6 +200,33 @@ LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x
private async Task Process(List<UserRoot> roots, BulkSatDownloadInput input)
{
//PO20220311: first time a call is made to download satellite images or statistics, an empty list is returned
//If we wait a bit longer, e.g. 10 secs, then e.g. a list of 3 images may be returned
//If we wait still longer, maybe 4 images.
//The solution implemented below is to fire calls as long as the number of images returned keeps increasing
//While in between each call, sleep for sleepSecs
//Continue this until the number no longer increases or the maximum number of calls has been reached
//If you set sleepSecs to a very low value, e.g. 5 secs, then after 1 call you might get images and after 2nd call still zero images.
//to be on the safe side, better bit higher value.
//Just accept this may take a while, have a coffee, we suggest sleepSecs = 30;
int sleepSecs = 30;
int callCntMax = 4 * 60 / sleepSecs; //4*60 = max 4 minutes
//For example we may set: "sleepSecs = 10;" and "callCntMax = 24;" and following result:
//Call no: 1. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 1: Received 2 images
//Call no: 2. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 2: Received 7 images
//Call no: 3. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 3: Received 7 images
//And the firing of calls would stop because the number of images returned is no longer increasing
//In the worst case, this could would lead to a total sleeping period of "sleepSecsSum = sleepSecs * callCntMax" seconds. After that we give up
//PO20230801: I also tried creating a cropfieldItem with startDate '2017-01-01' and endDate '2023-08-01'
//so that only one RunSatelliteTask would need to be executed and statistics would be returned for the e.g. 233 images in this period from start to end date
//instead of running 7 tasks (one per year) for a single field
//But code doing that returned much less images than those 233 records which I should be getting.
//So in the end, stick to downloading stats per year, even if it is for the same location in multiple years
string cropfielditemcode;
string satellitetaskcode;
Item cropfieldItem;
@ -222,6 +258,10 @@ LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x
DateTime lastDownloadedSatelliteDate = input.lastdownloadedimagedate;
cropfielditemcode = input.cropfielditemcode;
satellitetaskcode = input.satellitetaskcode;
int satelliteItemsCropYearCntPrev;
int satelliteItemsCropYearCnt;
int callCnt;
int sleepSecsSum;
LoadSettings(settingsfile);
@ -309,23 +349,80 @@ LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x
// TODO also log satellitetaskcode to settings, how?
// SaveSettings(settingsfile);
// Getting satellite items
// Getting satellite items. Only for years for which available
satelliteItemsCropYearCntPrev = 0;
satelliteItemsCropYearCnt = 0;
sleepSecsSum = 0;
satelliteItemsCropYear = null;
if (cropYear >= firstAvailableYear && cropYear <= DateTime.Now.Year)
{
_logger.LogInformation(string.Format($"Running FindSatelliteItems for cropfieldItem.Code '{cropfieldItem.Code}', SatelliteTaskCode '{satellitetaskcode}'"));
//Call first time
callCnt = 1;
//if callCntMax == 0 then don't sleep
//if callCntMax = 1 then sleep first 1x
if (callCntMax > 0)
{
_logger.LogInformation($"Call no: {callCnt}. Giving FarmMaps {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
sleepSecsSum = sleepSecsSum + sleepSecs;
}
satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, satellitetaskcode);
satelliteItemsCropYearCntPrev = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCntPrev} images");
callCnt++;
satelliteItemsCropYearCnt = satelliteItemsCropYearCntPrev;
//if callCntMax > 1 then sleep untill (1) no more increase in number of images received OR (2) maximum number of calls reached
if (callCntMax > 1)
{
//Call second time
_logger.LogInformation($"Call no: {callCnt}. Giving FarmMaps another {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, satellitetaskcode);
satelliteItemsCropYearCnt = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCnt} images");
sleepSecsSum = sleepSecsSum + sleepSecs;
//As long as there is progress, keep calling
callCnt++;
while (callCnt <= callCntMax && (satelliteItemsCropYearCnt == 0 || satelliteItemsCropYearCnt > satelliteItemsCropYearCntPrev))
{
_logger.LogInformation($"Surprise! The longer we wait, the more images we get. Sleep and call once more");
satelliteItemsCropYearCntPrev = satelliteItemsCropYearCnt;
_logger.LogInformation($"Call no: {callCnt} (max: {callCntMax}). Giving FarmMaps another {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, satellitetaskcode);
satelliteItemsCropYearCnt = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCnt} images");
callCnt++;
sleepSecsSum = sleepSecsSum + sleepSecs;
}
}
}
else
{
_logger.LogWarning($"// FarmmapsBulkSatDownload: crop year {cropYear} is out of bounds. No stats will be written!");
}
if (satelliteItemsCropYearCnt == 0)
{
_logger.LogWarning($"// FarmmapsBulkSatDownload: after calling one or more times and " +
$"sleeping in total {sleepSecsSum} seconds, still no images found. " +
$"Please check your settings for parameters callCntMax and sleepSecs in FarmmapsBulkSatDownload.cs or contact FarmMaps");
}
// Checking if satellite items found
satelliteItemsAvailable = true;
if (satelliteItemsCropYear == null)
{
satelliteItemsAvailable = false;
_logger.LogInformation($"No satellite tiffs found for fieldName '{fieldName}', cropYear {cropYear}, cropfielditemcode '{cropfielditemcode}'");
_logger.LogInformation($"// FarmmapsBulkSatDownload: No satellite tiffs found for fieldName '{fieldName}', cropYear {cropYear}, cropfielditemcode '{cropfielditemcode}'");
}
else
{
if (satelliteItemsCropYear.Count == 0)
{
satelliteItemsAvailable = false;
_logger.LogInformation($"No satellite tiffs found for fieldName '{fieldName}', cropYear {cropYear}, cropfielditemcode '{cropfielditemcode}'");
_logger.LogInformation($"// FarmmapsBulkSatDownload: No satellite tiffs found for fieldName '{fieldName}', cropYear {cropYear}, cropfielditemcode '{cropfielditemcode}'");
}
}
@ -335,10 +432,10 @@ LIMIT 5;", schemaname, parceltablename, groenmonitorlatestviewname); //LIMIT x
// Download statistics to a single csv file
if (satelliteItemsAvailable && downloadFolder != null && fileNameStats != null)
{
// Write statistics for all images for all fieldNane and cropYear to a single csv file, fileNameStats
// Write statistics for all images for all fieldName and cropYear to a single csv file, fileNameStats
_logger.LogInformation($"Downloading stats for field '{fieldName}' in cropyear {cropYear} to {fileNameStats}");
string downloadedStats = await _generalService.DownloadSatelliteStats(satelliteItemsCropYear, fieldName, satelliteBands, downloadFolder);
// Add contents of this csv file to thee single large csv file
// Add contents of this csv file to the single large csv file
var retainedLines = File.ReadAllLines(downloadedStats).Skip(1);
File.AppendAllLines(fileNameStats, retainedLines);
File.Delete(downloadedStats);

323
FarmmapsBulkSatDownload/BulkSatDownloadInput.json
View File

@ -1,46 +1,44 @@
[
{
"fieldName": "5641", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 1999, //For testing a year for which we know no satellite data available, program shouldn't crash
"fieldID": 5641,
"SatelliteBands": [ "wdvi", "ndvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "1999-01-01", //downloads images from this date till end of the year
"fieldName": "MyField_1", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2023,
"fieldID": 1,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2023-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 3.37837807779104, 51.3231095796538 ],
[ 3.38065689232502, 51.3212527499355 ],
[ 3.38022924592256, 51.3210683536359 ],
[ 3.37980548452565, 51.3208801127141 ],
[ 3.37959556105776, 51.3207540143696 ],
[ 3.3793691292654, 51.3205959677371 ],
[ 3.37822219207335, 51.3215667913007 ],
[ 3.37816999925795, 51.3216109809456 ],
[ 3.37646704574705, 51.3208025481261 ],
[ 3.37646695791282, 51.3208025061493 ],
[ 3.37608401443192, 51.3206231652693 ],
[ 3.37607169507628, 51.3206173959751 ],
[ 3.37606021048754, 51.320612017601 ],
[ 3.37582728410659, 51.3205029306946 ],
[ 3.37580409779263, 51.3206502985963 ],
[ 3.37575872019649, 51.3207993094705 ],
[ 3.37575476634361, 51.3208122883487 ],
[ 3.37571181656268, 51.3208797459348 ],
[ 3.3756624532907, 51.3209415238446 ],
[ 3.37557609963811, 51.3210110142077 ],
[ 3.37541089899821, 51.3211055871218 ],
[ 3.37477516102591, 51.3214102985009 ],
[ 3.37473173914127, 51.3214311108204 ],
[ 3.37455904622072, 51.3215138815012 ],
[ 3.37415098054777, 51.3217199232877 ],
[ 3.37313700916272, 51.3222422862785 ],
[ 3.37748824689601, 51.3242852920348 ],
[ 3.37749760805371, 51.3242713084009 ],
[ 3.37811903757028, 51.3233437635596 ],
[ 3.37818758851947, 51.3232647797363 ],
[ 3.37823803668144, 51.3232236798646 ],
[ 3.37837807779104, 51.3231095796538 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
"downloadFolder": "C:\\workdir\\groenmonitor\\", //if not yet existing this folder will be created
"fileNameStats": "BulkSatDownload.csv", //if file exists, probably will be overwritten. Check code in BulkSatDownloadApplication.cs
"database": null, // keep null to work with json and csv. Check code in BulkSatDownloadApplication.cs if reading/writing to/from database
"schemaname": null,
"cropfieldtable": null,
"satelllitetable": null
},
{
"fieldName": "MyField_2", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2022, // for testing same field last year (i.e. 2021)
"fieldID": 2,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2022-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
@ -52,47 +50,20 @@
"satelllitetable": null
},
{
"fieldName": "5641", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2021, //For testing a year for which we know no satellite data available, program shouldn't crash
"fieldID": 5641,
"SatelliteBands": [ "wdvi", "ndvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"fieldName": "MyField_3", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2021,
"fieldID": 3,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2021-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 3.37837807779104, 51.3231095796538 ],
[ 3.38065689232502, 51.3212527499355 ],
[ 3.38022924592256, 51.3210683536359 ],
[ 3.37980548452565, 51.3208801127141 ],
[ 3.37959556105776, 51.3207540143696 ],
[ 3.3793691292654, 51.3205959677371 ],
[ 3.37822219207335, 51.3215667913007 ],
[ 3.37816999925795, 51.3216109809456 ],
[ 3.37646704574705, 51.3208025481261 ],
[ 3.37646695791282, 51.3208025061493 ],
[ 3.37608401443192, 51.3206231652693 ],
[ 3.37607169507628, 51.3206173959751 ],
[ 3.37606021048754, 51.320612017601 ],
[ 3.37582728410659, 51.3205029306946 ],
[ 3.37580409779263, 51.3206502985963 ],
[ 3.37575872019649, 51.3207993094705 ],
[ 3.37575476634361, 51.3208122883487 ],
[ 3.37571181656268, 51.3208797459348 ],
[ 3.3756624532907, 51.3209415238446 ],
[ 3.37557609963811, 51.3210110142077 ],
[ 3.37541089899821, 51.3211055871218 ],
[ 3.37477516102591, 51.3214102985009 ],
[ 3.37473173914127, 51.3214311108204 ],
[ 3.37455904622072, 51.3215138815012 ],
[ 3.37415098054777, 51.3217199232877 ],
[ 3.37313700916272, 51.3222422862785 ],
[ 3.37748824689601, 51.3242852920348 ],
[ 3.37749760805371, 51.3242713084009 ],
[ 3.37811903757028, 51.3233437635596 ],
[ 3.37818758851947, 51.3232647797363 ],
[ 3.37823803668144, 51.3232236798646 ],
[ 3.37837807779104, 51.3231095796538 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
@ -104,47 +75,20 @@
"satelllitetable": null
},
{
"fieldName": "5641", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"fieldName": "MyField_4", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2020,
"fieldID": 5641,
"SatelliteBands": [ "wdvi", "ndvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"fieldID": 4,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2020-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 3.37837807779104, 51.3231095796538 ],
[ 3.38065689232502, 51.3212527499355 ],
[ 3.38022924592256, 51.3210683536359 ],
[ 3.37980548452565, 51.3208801127141 ],
[ 3.37959556105776, 51.3207540143696 ],
[ 3.3793691292654, 51.3205959677371 ],
[ 3.37822219207335, 51.3215667913007 ],
[ 3.37816999925795, 51.3216109809456 ],
[ 3.37646704574705, 51.3208025481261 ],
[ 3.37646695791282, 51.3208025061493 ],
[ 3.37608401443192, 51.3206231652693 ],
[ 3.37607169507628, 51.3206173959751 ],
[ 3.37606021048754, 51.320612017601 ],
[ 3.37582728410659, 51.3205029306946 ],
[ 3.37580409779263, 51.3206502985963 ],
[ 3.37575872019649, 51.3207993094705 ],
[ 3.37575476634361, 51.3208122883487 ],
[ 3.37571181656268, 51.3208797459348 ],
[ 3.3756624532907, 51.3209415238446 ],
[ 3.37557609963811, 51.3210110142077 ],
[ 3.37541089899821, 51.3211055871218 ],
[ 3.37477516102591, 51.3214102985009 ],
[ 3.37473173914127, 51.3214311108204 ],
[ 3.37455904622072, 51.3215138815012 ],
[ 3.37415098054777, 51.3217199232877 ],
[ 3.37313700916272, 51.3222422862785 ],
[ 3.37748824689601, 51.3242852920348 ],
[ 3.37749760805371, 51.3242713084009 ],
[ 3.37811903757028, 51.3233437635596 ],
[ 3.37818758851947, 51.3232647797363 ],
[ 3.37823803668144, 51.3232236798646 ],
[ 3.37837807779104, 51.3231095796538 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
@ -156,47 +100,20 @@
"satelllitetable": null
},
{
"fieldName": "5641", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"fieldName": "MyField_5", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2019,
"fieldID": 5641,
"SatelliteBands": [ "wdvi", "ndvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"fieldID": 5,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2019-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 3.37837807779104, 51.3231095796538 ],
[ 3.38065689232502, 51.3212527499355 ],
[ 3.38022924592256, 51.3210683536359 ],
[ 3.37980548452565, 51.3208801127141 ],
[ 3.37959556105776, 51.3207540143696 ],
[ 3.3793691292654, 51.3205959677371 ],
[ 3.37822219207335, 51.3215667913007 ],
[ 3.37816999925795, 51.3216109809456 ],
[ 3.37646704574705, 51.3208025481261 ],
[ 3.37646695791282, 51.3208025061493 ],
[ 3.37608401443192, 51.3206231652693 ],
[ 3.37607169507628, 51.3206173959751 ],
[ 3.37606021048754, 51.320612017601 ],
[ 3.37582728410659, 51.3205029306946 ],
[ 3.37580409779263, 51.3206502985963 ],
[ 3.37575872019649, 51.3207993094705 ],
[ 3.37575476634361, 51.3208122883487 ],
[ 3.37571181656268, 51.3208797459348 ],
[ 3.3756624532907, 51.3209415238446 ],
[ 3.37557609963811, 51.3210110142077 ],
[ 3.37541089899821, 51.3211055871218 ],
[ 3.37477516102591, 51.3214102985009 ],
[ 3.37473173914127, 51.3214311108204 ],
[ 3.37455904622072, 51.3215138815012 ],
[ 3.37415098054777, 51.3217199232877 ],
[ 3.37313700916272, 51.3222422862785 ],
[ 3.37748824689601, 51.3242852920348 ],
[ 3.37749760805371, 51.3242713084009 ],
[ 3.37811903757028, 51.3233437635596 ],
[ 3.37818758851947, 51.3232647797363 ],
[ 3.37823803668144, 51.3232236798646 ],
[ 3.37837807779104, 51.3231095796538 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
@ -208,47 +125,95 @@
"satelllitetable": null
},
{
"fieldName": "5641", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2018, //little to no images for 2018
"fieldID": 5641,
"SatelliteBands": [ "wdvi", "ndvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"fieldName": "MyField_6", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2018,
"fieldID": 6,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2018-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 3.37837807779104, 51.3231095796538 ],
[ 3.38065689232502, 51.3212527499355 ],
[ 3.38022924592256, 51.3210683536359 ],
[ 3.37980548452565, 51.3208801127141 ],
[ 3.37959556105776, 51.3207540143696 ],
[ 3.3793691292654, 51.3205959677371 ],
[ 3.37822219207335, 51.3215667913007 ],
[ 3.37816999925795, 51.3216109809456 ],
[ 3.37646704574705, 51.3208025481261 ],
[ 3.37646695791282, 51.3208025061493 ],
[ 3.37608401443192, 51.3206231652693 ],
[ 3.37607169507628, 51.3206173959751 ],
[ 3.37606021048754, 51.320612017601 ],
[ 3.37582728410659, 51.3205029306946 ],
[ 3.37580409779263, 51.3206502985963 ],
[ 3.37575872019649, 51.3207993094705 ],
[ 3.37575476634361, 51.3208122883487 ],
[ 3.37571181656268, 51.3208797459348 ],
[ 3.3756624532907, 51.3209415238446 ],
[ 3.37557609963811, 51.3210110142077 ],
[ 3.37541089899821, 51.3211055871218 ],
[ 3.37477516102591, 51.3214102985009 ],
[ 3.37473173914127, 51.3214311108204 ],
[ 3.37455904622072, 51.3215138815012 ],
[ 3.37415098054777, 51.3217199232877 ],
[ 3.37313700916272, 51.3222422862785 ],
[ 3.37748824689601, 51.3242852920348 ],
[ 3.37749760805371, 51.3242713084009 ],
[ 3.37811903757028, 51.3233437635596 ],
[ 3.37818758851947, 51.3232647797363 ],
[ 3.37823803668144, 51.3232236798646 ],
[ 3.37837807779104, 51.3231095796538 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
"downloadFolder": "C:\\workdir\\groenmonitor\\",
"fileNameStats": "BulkSatDownload.csv",
"database": null,
"schemaname": null,
"cropfieldtable": null,
"satelllitetable": null
},
{
"fieldName": "MyField_6", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson
"cropYear": 2017,
"fieldID": 7,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2017-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
"downloadFolder": "C:\\workdir\\groenmonitor\\",
"fileNameStats": "BulkSatDownload.csv",
"database": null,
"schemaname": null,
"cropfieldtable": null,
"satelllitetable": null
},
{
"fieldName": "MyField_8", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson. Actually no Satellite data before 2017. This here to illustrate the program does not crash
"cropYear": 2016,
"fieldID": 8,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2016-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},
"downloadFolder": "C:\\workdir\\groenmonitor\\",
"fileNameStats": "BulkSatDownload.csv",
"database": null,
"schemaname": null,
"cropfieldtable": null,
"satelllitetable": null
},
{
"fieldName": "MyField_9", // FarmMaps minimum needs are: fieldName, cropYear & geometryJson. Actually no Satellite data before 2017. This here to illustrate the program does not crash
"cropYear": 2015,
"fieldID": 9,
"SatelliteBands": [ "ci-red", "ndvi", "wdvi" ], // ["ndvi"] or ["wdvi"] or both: [ "wdvi", "ndvi" ]
"lastdownloadedimagedate": "2015-01-01", //downloads images from this date till end of the year
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
},

178
FarmmapsBulkSatDownload/ShowGeotiff.r
View File

@ -1,178 +0,0 @@
# ShowGeotiff.r
# I downloaded and calculated the stats for the polygon defined in C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
# in which I set "SatelliteBand": "wdvi" and in which in the console I requested the image for date '2020-09-22'
# FarmmapsBulkSatDownload generates many files. Here is what I tried when inputing the same field for a number of years using BulkSatDownloadInput.json
# see list below
library(raster)
library(sf)
library(rgdal)
setwd("C:/workdir/groenmonitor/DataDownload/")
# FarmmapsDataDownload and BulkSatDownload can be used to download zip files with inside two files:
fileGeotiff <- "wenr.tif"
fileJpg <- "thumbnail.jpg"
# Here is what I tried when inputing the same field for a number of years:
# fileGeotiff <- "wheat_fld5641_20210224.tif" # 2 files for year 2021. This file is a nice example having in upperleft corner no data
# fileGeotiff <- "wheat_fld5641_20210331.tif" # 2 files for year 2021
# fileGeotiff <- "wheat_fld5641_20200321.tif" # 14 files for year 2020, earliest
# fileGeotiff <- "wheat_fld5641_20200922.tif" # 14 files for year 2020, latest
# fileGeotiff <- "wheat_fld5641_20190121.tif" # 9 files for year 2019, earliest
# fileGeotiff <- "wheat_fld5641_20191117.tif" # 9 files for year 2019, latest
# 1 file for year 2018, with error message 'End of Central Directory record could not be found' and invalid wheat_fld5641_20180630.zip
# fileGeotiff <- "wheat_fld5641_20170526.tif" # 1 file for year 2017
# Zero files for 2016
lenfilename <- nchar(fileGeotiff)
year <- substr(fileGeotiff,lenfilename-11,lenfilename-8)
imgdate <- substr(fileGeotiff,lenfilename-11,lenfilename-4)
# The thumbnail has the polygon clipped out, has 1 layer, no crs and the mean value is not the mean wdvi we are looking for
r.thumbnail <- raster(fileJpg)
plot(r.thumbnail)
crs(r.thumbnail)
#CRS arguments: NA
cellStats(r.thumbnail,'mean') #87.5128 # nonsense
stk.wenr <- stack(x=fileGeotiff)
# plot(stk.wenr) shows 5 plots (5 bands)
# I think these are:
# 1. ndvi (since it runs from 0 to 1)
# 2. wdvi (since it runs from 0 to 0.5)
# 3-5: RGB (since they run from 0 to 255)
plot(stk.wenr)
# CRS arguments:
# +proj=sterea +lat_0=52.1561605555556 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +units=m +no_defs
# Or use st_crs(stk.wenr) to get more info, but no EPSG code in there.
# Likely it is epsg:28992 (Amersfoort)
crs(stk.wenr)
stk.wenr <- projectRaster(stk.wenr, crs = CRS('+init=EPSG:28992'))
crs(stk.wenr)
# Looks the same but strangely, if we don't do projectRaster(stk.wenr, crs = CRS('+init=EPSG:28992')), we find below the bottom left corner of the polygon missing
r.wenr.rd.wdvi <- subset(stk.wenr,2)
dev.off()
plot(r.wenr.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
cellStats(r.wenr.rd.wdvi,'mean') #0.1350561
# Furthermore we can see
# shows coordinates in RD
# returns a rectangle, thus the shape of the polygon submitted is not clipped.
# The polygon was provided in WGS84. Let's draw it on top.
# First convert the raster to WGS84
r.wenr.wgs84.wdvi <- projectRaster(r.wenr.rd.wdvi, crs = CRS('+init=EPSG:4326'))
# Draw a polygon on top of the raster
# Example polygon p1
# p1 <- data.frame(id = 1, wkt = 'POLYGON((4.963 52.801, 4.966 52.801, 4.966 52.803, 4.963 52.803, 4.963 52.801))')
# p1 <- st_as_sf(p1, wkt = 'wkt', crs = targetcrs)
# plot(p1,add=TRUE, col="transparent",border="black")
# Draw the polygon on top of the raster
# Polygon p2 from C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
p2 <- data.frame(id = 1, wkt = gsub("\n","",'POLYGON((
4.960707146896585 52.800583669708487,
4.960645975538824 52.800470217610922,
4.962140695752897 52.799177147194797,
4.967523821195745 52.801502400041208,
4.966336768950911 52.802543735879809,
4.961711880764330 52.801009996856429,
4.960707146896585 52.800583669708487))'))
# Polygon p2 from C:\git\FarmMapsApiClient_WURtest\FarmmapsBulkSatDownload\BulkSatDownloadInput.json
p2 <- data.frame(id = 1, wkt = gsub("\n","",'POLYGON((
3.37837807779104 51.3231095796538,
3.38065689232502 51.3212527499355,
3.38022924592256 51.3210683536359,
3.37980548452565 51.3208801127141,
3.37959556105776 51.3207540143696,
3.3793691292654 51.3205959677371,
3.37822219207335 51.3215667913007,
3.37816999925795 51.3216109809456,
3.37646704574705 51.3208025481261,
3.37646695791282 51.3208025061493,
3.37608401443192 51.3206231652693,
3.37607169507628 51.3206173959751,
3.37606021048754 51.320612017601,
3.37582728410659 51.3205029306946,
3.37580409779263 51.3206502985963,
3.37575872019649 51.3207993094705,
3.37575476634361 51.3208122883487,
3.37571181656268 51.3208797459348,
3.3756624532907 51.3209415238446,
3.37557609963811 51.3210110142077,
3.37541089899821 51.3211055871218,
3.37477516102591 51.3214102985009,
3.37473173914127 51.3214311108204,
3.37455904622072 51.3215138815012,
3.37415098054777 51.3217199232877,
3.37313700916272 51.3222422862785,
3.37748824689601 51.3242852920348,
3.37749760805371 51.3242713084009,
3.37811903757028 51.3233437635596,
3.37818758851947 51.3232647797363,
3.37823803668144 51.3232236798646,
3.37837807779104 51.3231095796538))'))
p2.wgs84 <- st_as_sf(p2, wkt = 'wkt', crs = CRS('+init=EPSG:4326'))
# Or other way round, in RD Amersfoort. That looks ok
p2.rd <- st_transform(p2.wgs84, "+init=epsg:28992")
# Have a look at both
# wg84
dev.off()
plot(r.wenr.wgs84.wdvi,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
plot(p2.wgs84,add=TRUE, col="transparent",border="red")
# RD
dev.off()
plot(r.wenr.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
plot(p2.rd,add=TRUE, col="transparent",border="red")
#Let's clip the polygon
r.wenr.rd.wdvi.pol <- mask(r.wenr.rd.wdvi,p2.rd)
r.wenr.wgs84.wdvi.pol <- mask(r.wenr.wgs84.wdvi,p2.wgs84)
dev.off()
plot(r.wenr.wgs84.wdvi.pol,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
plot(p2.wgs84,add=TRUE, col="transparent",border="red")
#That's what we want! Now compare the stats
cellStats(r.wenr.rd.wdvi,'mean') # [1] 0.1350561 # Stats from rectangle, RD
cellStats(r.wenr.wgs84.wdvi,'mean') # [1] 0.1351411 # Stats from rectangle, WGS84
cellStats(r.wenr.rd.wdvi.pol,'mean') # [1] 0.05723957 # Stats from raster clipped by polygon, RD
cellStats(r.wenr.wgs84.wdvi.pol,'mean') # [1] 0.05723607 # Stats from raster clipped by polygon, WGS84
# file SatelliteDataStatistics_test_satData_wdvi_2020-09-22.csv
# "mean": 0.057430520945401985 # SatelliteDataStatistics_test_satData_wdvi_2020.csv returns stats for the clipped raster (.pol). 'mean' almost the same, maybe
# cellStats cannot return median, just a few stats.
cellStats(r.wenr.wgs84.wdvi.pol,'median') # Error in .local(x, stat, ...) : invalid 'stat'. Should be sum, min, max, sd, mean, or 'countNA'
r.wenr.wgs84.wdvi.vals <- values(r.wenr.wgs84.wdvi)
median(r.wenr.wgs84.wdvi.vals) # [1] NA
median(r.wenr.wgs84.wdvi.vals,na.rm=TRUE) # [1] 0.076
r.wenr.wgs84.wdvi.pol.vals <- values(r.wenr.wgs84.wdvi.pol)
median(r.wenr.wgs84.wdvi.pol.vals) # [1] NA
median(r.wenr.wgs84.wdvi.pol.vals,na.rm=TRUE) # [1] 0.048
# "median": 0.04800000041723251 # SatelliteDataStatistics_test_satData_wdvi_2020.csv returns stats for the clipped raster (.pol).
# An image may contain NA values. Check:
cellStats(r.wenr.wgs84.wdvi,'countNA') # [1] 22956
ncell(r.wenr.wgs84.wdvi) # [1] 221696
cellStats(r.wenr.wgs84.wdvi,'countNA') / ncell(r.wenr.wgs84.wdvi) # [1] 0.1035472 # 10% no data? doesn't show in the plot?
cellStats(r.wenr.wgs84.wdvi.pol,'countNA') # [1] 147387
summary(r.wenr.wgs84.wdvi.pol.vals) # shows the same: NA's: 147387
ncell(r.wenr.wgs84.wdvi.pol) # [1] 221696
cellStats(r.wenr.wgs84.wdvi.pol,'countNA') / ncell(r.wenr.wgs84.wdvi.pol) # [1] 0.6648158 # 66% no data? doesn't show in the plot?
# The project FarmmapsNbs can generate a wenr.tif file, application.tif, uptake.tif (in rtest1.uptake.zip)and shape.shp (in rtest1.taskmap.zip)
r.application <- raster("C:/git/FarmMapsApiClient_WURtest/FarmmapsNbs/bin/Debug/netcoreapp3.1/Downloads/application.tif")
dev.off()
plot(r.application)
plot(p2.rd,add=TRUE, col="transparent",border="red")
# The application.tif file is a rectangle (polygon not yet clipped), in projection Amersfoort RD New (EPSG:28992)
r.uptake <- raster("C:/git/FarmMapsApiClient_WURtest/FarmmapsNbs/bin/Debug/netcoreapp3.1/Downloads/uptake.tif")
dev.off()
plot(r.uptake)
plot(p2.rd,add=TRUE, col="transparent",border="red")
# The uptake.tif file is a rectangle (polygon not yet clipped), in projection Amersfoort RD New (EPSG:28992)
shp.wgs84 <- readOGR(dsn="C:/git/FarmMapsApiClient_WURtest/FarmmapsNbs/bin/Debug/netcoreapp3.1/Downloads", layer="shape")
crs(shp.wgs84)
# CRS arguments: +proj=longlat +datum=WGS84 +no_defs
dev.off()
plot(r.wenr.wgs84.wdvi,main="wdvi",xlab="LON",ylab="LAT")
plot(shp.wgs84,add=TRUE, col="transparent",border="black")
plot(p2.wgs84,add=TRUE, col="transparent",border="red")
# The shape file is in WGS84

125
FarmmapsDataDownload/DataDownloadApplication.cs
View File

@ -38,7 +38,7 @@ namespace FarmmapsDataDownload
public async Task RunAsync()
{
var fieldsInputJson = File.ReadAllText("DataDownloadInput.json");
string fieldsInputJson = File.ReadAllText("DataDownloadInput.json");
List<DataDownloadInput> fieldsInputs = JsonConvert.DeserializeObject<List<DataDownloadInput>>(fieldsInputJson);
@ -61,6 +61,28 @@ namespace FarmmapsDataDownload
private async Task Process(List<UserRoot> roots, DataDownloadInput input)
{
//PO20220311: first time a call is made to download satellite images or statistics, an empty list is returned
//If we wait a bit longer, e.g. 10 secs, then e.g. a list of 3 images may be returned
//If we wait still longer, maybe 4 images.
//The solution implemented below is to fire calls as long as the number of images returned keeps increasing
//While in between each call, sleep for sleepSecs
//Continue this until the number no longer increases or the maximum number of calls has been reached
//Out of politeness, don't be too impatient. Don't set sleepSecs to 5 or 10 or 30 secs. Just accept this may take a while, have a coffee, we suggest sleepSecs = 60;
int sleepSecs = 60;
int callCntMax = 4;
//For example we may set: "sleepSecs = 10;" and "callCntMax = 24;" and following result:
//Call no: 1. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 1: Received 2 images
//Call no: 2. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 2: Received 7 images
//Call no: 3. Giving FarmMaps 10 seconds to get SatelliteItems...
//Call no: 3: Received 7 images
//And the firing of calls would stop because the number of images returned is no longer increasing
//In the worst case, this could would lead to a total sleeping period of "sleepSecsSum = sleepSecs * callCntMax" seconds. After that we give up
//This is an ugly fix. Neater would if FarmMaps would just take a bit longer and then do always deliver all satellite images on first call.
//Once this has been fixed on the side of FarmMaps we can set callCntMax = 0 and the code below will work smoothly without any sleeping
string downloadFolder = input.DownloadFolder;
if (string.IsNullOrEmpty(downloadFolder)) {
downloadFolder = "Downloads";
@ -74,7 +96,8 @@ namespace FarmmapsDataDownload
var fieldName = input.fieldName;
bool storeSatelliteStatistics = input.StoreSatelliteStatisticsSingleImage;
bool storeSatelliteStatisticsCropYear = input.StoreSatelliteStatisticsCropYear;
List<string> SatelliteBands = new List<string>(1) { input.SatelliteBand };
//List<string> SatelliteBands = new List<string>(1) { input.SatelliteBand };
List<string> satelliteBands = input.SatelliteBands;
string headerLineStats = $"FieldName,satelliteDate,satelliteBand,max,min,mean,mode,median,stddev,minPlus,curtosis,maxMinus,skewness,variance,populationCount,variationCoefficient,confidenceIntervalLow, confidenceIntervalHigh,confidenceIntervalErrorMargin" + Environment.NewLine;
@ -166,12 +189,58 @@ namespace FarmmapsDataDownload
SaveSettings(settingsfile);
}
// Select all satellite items
//Call first time
int callCnt = 1;
int sleepSecsSum = 0;
//if callCntMax == 0 then don't sleep
//if callCntMax = 1 then sleep first 1x
if (callCntMax > 0)
{
_logger.LogInformation($"Call no: {callCnt}. Giving FarmMaps {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
sleepSecsSum = sleepSecsSum + sleepSecs;
}
List<Item> satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, _settings.SatelliteTaskCode);
int satelliteItemsCropYearCntPrev = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCntPrev} images");
callCnt++;
int satelliteItemsCropYearCnt = satelliteItemsCropYearCntPrev;
//if callCntMax > 1 then sleep untill (1) no more increase in number of images received OR (2) maximum number of calls reached
if (callCntMax > 1)
{
//Call second time
_logger.LogInformation($"Call no: {callCnt}. Giving FarmMaps another {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, _settings.SatelliteTaskCode);
satelliteItemsCropYearCnt = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCnt} images");
sleepSecsSum = sleepSecsSum + sleepSecs;
//As long as there is progress, keep calling
callCnt++;
while (callCnt <= callCntMax && (satelliteItemsCropYearCnt == 0 || satelliteItemsCropYearCnt > satelliteItemsCropYearCntPrev))
{
_logger.LogInformation($"Surprise! The longer we wait, the more images we get. Sleep and call once more");
satelliteItemsCropYearCntPrev = satelliteItemsCropYearCnt;
_logger.LogInformation($"Call no: {callCnt} (max: {callCntMax}). Giving FarmMaps another {sleepSecs} seconds to get SatelliteItems...");
System.Threading.Thread.Sleep(1000 * sleepSecs);
satelliteItemsCropYear = await _generalService.FindSatelliteItems(cropfieldItem, _settings.SatelliteTaskCode);
satelliteItemsCropYearCnt = satelliteItemsCropYear.Count;
_logger.LogInformation($"Call no: {callCnt}. Received {satelliteItemsCropYearCnt} images");
callCnt++;
sleepSecsSum = sleepSecsSum + sleepSecs;
}
}
if (satelliteItemsCropYearCnt == 0)
{
_logger.LogWarning($"DataDownloadApplication.cs: after calling one or more times and " +
$"sleeping in total {sleepSecsSum} seconds, still no images found. " +
$"Please check your settings for parameters callCntMax and sleepSecs in DataDownloadApplication.cs or contact FarmMaps");
}
satelliteItemsCropYear = satelliteItemsCropYear.OrderBy(x => x.DataDate).ToList();
if (input.StoreSatelliteStatisticsSingleImage == true) {
if (input.StoreSatelliteStatisticsSingleImage == true && satelliteItemsCropYearCnt > 0) {
_logger.LogInformation("Available satellite images:");
var count = 0;
TimeSpan.FromSeconds(0.5);
@ -188,43 +257,49 @@ namespace FarmmapsDataDownload
var SatelliteDate = selectedSatelliteItem.DataDate.Value.ToString("yyyyMMdd");
string fileName = string.Format($"satelliteGeotiff_{fieldName}_{SatelliteDate}"); // no need to add satelliteBand in the name because the tif contains all bands
string fileNameZip = string.Format($"{fileName}.zip");
string fileNameGeotiff = string.Format($"{fileName}.tif");
await _farmmapsApiService.DownloadItemAsync(selectedSatelliteItem.Code, Path.Combine(downloadFolder, fileNameZip));
string fileNameZip = Path.Combine(downloadFolder, string.Format($"{fileName}.zip"));
await _farmmapsApiService.DownloadItemAsync(selectedSatelliteItem.Code, fileNameZip);
// Download a csv file with stats
List<Item> selectedSatalliteItems = new List<Item>(1) { selectedSatelliteItem };
List<Item> selectedSatelliteItems = new List<Item>(1) { selectedSatelliteItem };
string fileNameStats = Path.Combine(downloadFolder, string.Format($"satelliteStats_{fieldName}_{SatelliteDate}.csv"));
string downloadedStats = await _generalService.DownloadSatelliteStats(selectedSatalliteItems, fieldName, SatelliteBands, downloadFolder);
_logger.LogInformation($"First call to get DownloadSatelliteStats for selected image...");
string downloadedStats = await _generalService.DownloadSatelliteStats(selectedSatelliteItems, fieldName, satelliteBands, downloadFolder);
//rename the csv file with stats
//if the targe file already exists, delete it
File.Delete(fileNameStats);
//rename
File.Move(downloadedStats, fileNameStats);
// wenr.tif. Contains 5 layers: (1) ndvi, (2) wdvi, (3) Red, (4) Green and (5) Blue
// download the geotiffs. Returns a zip file with always these three files:
// data.dat.aux.xml
// name the tif file
string fileNameTifzipped = Path.Combine(downloadFolder, string.Format($"sentinelhub_{SatelliteDate}.tif"));
string fileNameGeotiff = Path.Combine(downloadFolder, string.Format($"sentinelhub_{fieldName}_{SatelliteDate}.tif"));
// download the geotiffs. Returns a zip file with always these two files:
// thumbnail.jpg
// wenr.tif. Contains 5 layers: (1) ndvi, (2) wdvi, (3) Red, (4) Green and (5) Blue
// sentinelhub_yyyyMMdd.tif. Contains 4 layers: (1) ndvi, (2) wdvi, (3) ci-red and (4) natural. Natural has 3 layers inside: redBand, blueBand and greenBand
if (true)
{
// Extract the file "wenr.tif" from zip, rename it to fileNameGeotiff
ZipFile.ExtractToDirectory(Path.Combine(downloadFolder, fileNameZip), downloadFolder, true);
File.Delete(Path.Combine(downloadFolder, fileNameGeotiff)); // Delete the fileNameGeotiff file if exists
File.Move(Path.Combine(downloadFolder, "wenr.tif"), Path.Combine(downloadFolder, fileNameGeotiff)); // Rename the oldFileName into newFileName
// Extract the file fileNameTifzipped from zip, rename it to fileNameGeotiff
ZipFile.ExtractToDirectory(fileNameZip, downloadFolder, true);
//if the targe file already exists, delete it
File.Delete(fileNameGeotiff);
//rename
File.Move(fileNameTifzipped, fileNameGeotiff);
// Cleanup
string[] filesToDelete = new string[] { fileNameZip, "wenr.tif", "thumbnail.jpg", "data.dat.aux.xml" };
foreach (string f in filesToDelete)
{
File.Delete(Path.Combine(downloadFolder, f));
File.Delete(fileNameZip);
File.Delete(Path.Combine(downloadFolder, "thumbnail.jpg"));
}
}
_logger.LogInformation($"Downloaded files {fileNameGeotiff} and {fileNameStats} to {downloadFolder}");
//_logger.LogInformation($"Downloaded files {fileNameGeotiff} and {fileNameStats} to {downloadFolder}");
_logger.LogInformation($"Downloaded files to {downloadFolder}");
}
if (input.StoreSatelliteStatisticsCropYear == true) {
string fileNameStats = Path.Combine(downloadFolder, string.Format($"satelliteStats_{fieldName}_{cropYear}.csv"));
File.Delete(fileNameStats);
string downloadedStats = await _generalService.DownloadSatelliteStats(satelliteItemsCropYear, fieldName, SatelliteBands, downloadFolder);
_logger.LogInformation($"First call to get DownloadSatelliteStats for whole cropYear...");
string downloadedStats = await _generalService.DownloadSatelliteStats(satelliteItemsCropYear, fieldName, satelliteBands, downloadFolder);
File.Move(downloadedStats, fileNameStats);
_logger.LogInformation($"Downloaded file {fileNameStats} with stats for field '{fieldName}', cropyear {cropYear}");
}

32
FarmmapsDataDownload/DataDownloadInput.json
View File

@ -1,34 +1,30 @@
[
{
"UseCreatedCropfield": true,
"outputFileName": "TestData",
"fieldName": "TestField",
"UseCreatedCropfield": false, // if false, program will make new CropfieldItemCode and SatelliteTaskCode; if true, the program will read CropfieldItemCode and SatelliteTaskCode from a file called "..\FarmmapsDataDownload\bin\Debug\netcoreapp3.1\Settings_{fieldName}.json", which will be faster
"outputFileName": "test_BvdTFieldlabG92",
"fieldName": "test_BvdTFieldlabG92",
"DownloadFolder": "Downloads", //"C:\\workdir\\groenmonitor\\", // "Downloads", -> if you just put "Downloads" the program will download to somewhere in ..\FarmMapsApiClient_WURtest\FarmmapsDataDownload\bin\Debug\netcoreapp3.1\Downloads\
"GetCropRecordings": true,
"GetCropRecordings": false,
"CrprecItem": "...", //item code of de crop recording parrent - can be found by opening the crop recording page of a field.
"GetShadowData": false,
"GetSatelliteData": false,
"SatelliteBand": "wdvi", // "natural", "ndvi" or "wdvi"
"StoreSatelliteStatisticsSingleImage": false,
"StoreSatelliteStatisticsCropYear": false,
"GetSatelliteData": true,
"SatelliteBands": [ "ndvi", "wdvi", "ci-red" ], // ["ndvi"] or ["wdvi"] or ["ci-red"] or multiple: [ "wdvi", "ndvi" ]
"StoreSatelliteStatisticsSingleImage": true,
"StoreSatelliteStatisticsCropYear": true,
"GetVanDerSatData": false,
"StoreVanDerSatStatistics": false,
"CropYear": 2020,
"CropYear": 2022,
"geometryJson": {
"type": "Polygon",
"coordinates": [
[
[ 4.960707146896585, 52.800583669708487 ],
[ 4.960645975538824, 52.800470217610922 ],
[ 4.962140695752897, 52.799177147194797 ],
[ 4.967523821195745, 52.801502400041208 ],
[ 4.966336768950911, 52.802543735879809 ],
[ 4.961711880764330, 52.801009996856429 ],
[ 4.960707146896585, 52.800583669708487 ]
[ 5.563472073408009, 52.547554398144172 ],
[ 5.567425915520115, 52.547725375100377 ],
[ 5.567917474269188, 52.540608459298582 ],
[ 5.563878143678981, 52.54048022658143 ],
[ 5.563472073408009, 52.547554398144172 ]
]
]
}
}
]

2
FarmmapsDataDownload/FarmmapsDataDownload.csproj
View File

@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>netcoreapp3.0</TargetFramework>
<TargetFramework>netcoreapp3.1</TargetFramework>
</PropertyGroup>
<ItemGroup>

3
FarmmapsDataDownload/Models/DataDownloadInput.cs
View File

@ -1,4 +1,5 @@
using System;
using System.Collections.Generic;
using Newtonsoft.Json.Linq;
namespace FarmmapsDataDownload.Models
@ -16,7 +17,7 @@ namespace FarmmapsDataDownload.Models
public string fieldName { get; set; }
public bool GetSatelliteData { get; set; }
public bool GetVanDerSatData { get; set; }
public string SatelliteBand { get; set; }
public List<string> SatelliteBands { get; set; }
public bool StoreSatelliteStatisticsSingleImage { get; set; }
public bool StoreSatelliteStatisticsCropYear { get; set; }
public bool StoreVanDerSatStatistics { get; set; }

114
FarmmapsDataDownload/ShowGeotiff.r Normal file
View File

@ -0,0 +1,114 @@
# ShowGeotiff.r
# Have a look at a downloaded satellite image and check if stats are correctly calculated
# I downloaded and calculated the stats for the polygon defined in C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
# in which I set "SatelliteBand": "wdvi" and in which in the console I requested the image for date '2022-03-08'
library(raster)
library(sf)
library(rgdal)
setwd("C:/git/FarmMapsApiClient_WURtest/FarmmapsDataDownload/bin/Debug/netcoreapp3.1/Downloads")
# FarmmapsDataDownload
fileGeotiff <- "sentinelhub_test_BvdTFieldlabG92_20220308.tif"
lenfilename <- nchar(fileGeotiff)
year <- substr(fileGeotiff,lenfilename-11,lenfilename-8)
imgdate <- substr(fileGeotiff,lenfilename-11,lenfilename-4)
stk.sentinelhub <- stack(x=fileGeotiff)
# plot(stk.sentinelhub) shows 6 plots (6 bands)
# 1. ndvi
# 2. wdvi Note wdvi-red
# 3. ci-red
# 4. natural: red
# 5. natural: green
# 6. natural: blue
names(stk.sentinelhub) <- c("ndvi","wdvired","ci-red","red","green","blue")
plot(stk.sentinelhub)
crs(stk.sentinelhub)
# CRS arguments: +proj=longlat +datum=WGS84 +no_defs
stk.sentinelhub.rd <- projectRaster(stk.sentinelhub, crs = CRS('+init=EPSG:28992'))
crs(stk.sentinelhub)
r.sentinelhub.rd.wdvi <- subset(stk.sentinelhub.rd,2)
dev.off()
plot(r.sentinelhub.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
cellStats(r.sentinelhub.rd.wdvi,'mean') # 0.2252725
# Convert the .rd.wdvi raster to WGS84
r.sentinelhub.wgs84.wdvi <- projectRaster(r.sentinelhub.rd.wdvi, crs = CRS('+init=EPSG:4326'))
# Draw a polygon on top of the raster
# Polygon pol from C:\git\FarmMapsApiClient_WURtest\FarmmapsDataDownload\DataDownloadInput.json
pol <- data.frame(id = 1, wkt = gsub("\n","",'POLYGON((
5.563472073408009 52.547554398144172,
5.567425915520115 52.547725375100377,
5.567917474269188 52.540608459298582,
5.563878143678981 52.54048022658143,
5.563472073408009 52.547554398144172
))'))
pol.wgs84 <- st_as_sf(pol, wkt = 'wkt', crs = CRS('+init=EPSG:4326'))
pol.rd <- st_transform(pol.wgs84, "+init=epsg:28992")
#Calculate approximate middle of polygon
res <- as.data.frame(do.call("rbind", lapply(st_geometry(pol.wgs84), st_bbox)))
res$latmid <- (res$ymax+res$ymin)/2.0
res$lonmid <- (res$xmax+res$xmin)/2.0
res
# xmin ymin xmax ymax latmid lonmid
# 1 5.563472 52.54048 5.567917 52.54773 52.5441 5.565695
# Have a look at both polygons
# wg84
dev.off()
plot(r.sentinelhub.wgs84.wdvi,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
plot(pol.wgs84,add=TRUE, col="transparent",border="red")
# RD
dev.off()
plot(r.sentinelhub.rd.wdvi,main=paste("wdvi",imgdate),xlab="RDX",ylab="RDY")
plot(pol.rd,add=TRUE, col="transparent",border="red")
# Clip the polygon from the full rectangle figure
r.sentinelhub.rd.wdvi.pol <- mask(r.sentinelhub.rd.wdvi,pol.rd)
r.sentinelhub.wgs84.wdvi.pol <- mask(r.sentinelhub.wgs84.wdvi,pol.wgs84)
dev.off()
plot(r.sentinelhub.wgs84.wdvi.pol,main=paste("wdvi",imgdate),xlab="LON",ylab="LAT")
plot(pol.wgs84,add=TRUE, col="transparent",border="red")
#That's what we want!
# Now compare the stats
cellStats(r.sentinelhub.wgs84.wdvi,'mean') # [1] 0.2250987 # Stats from rectangle, WGS84
cellStats(r.sentinelhub.rd.wdvi,'mean') # [1] 0.2252725 # Stats from rectangle, RD. Almost but not exactly same as above
cellStats(r.sentinelhub.wgs84.wdvi.pol,'mean') # [1] 0.2275067 # Stats from raster clipped by polygon, WGS84
cellStats(r.sentinelhub.rd.wdvi.pol,'mean') # [1] 0.2275073 # Stats from raster clipped by polygon, RD. Almost but not exactly same as above
# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
# "wdvi" "mean": 0.22744397204465
# Mean in csv corresponds with cellStats calculated from clipped tif!
# So while the tif returned is a non-clipped image, the downloaded statistics are from the clipped image
# Exactly as we wanted.
cellStats(r.sentinelhub.wgs84.wdvi.pol,'median') # Error in .local(x, stat, ...) : invalid 'stat'. Should be sum, min, max, sd, mean, or 'countNA'
r.sentinelhub.wgs84.wdvi.vals <- values(r.sentinelhub.wgs84.wdvi)
median(r.sentinelhub.wgs84.wdvi.vals) # [1] NA
median(r.sentinelhub.wgs84.wdvi.vals,na.rm=TRUE) # [1] 0.2318
r.sentinelhub.wgs84.wdvi.pol.vals <- values(r.sentinelhub.wgs84.wdvi.pol)
median(r.sentinelhub.wgs84.wdvi.pol.vals) # [1] NA
median(r.sentinelhub.wgs84.wdvi.pol.vals,na.rm=TRUE) # [1] 0.2338
# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
# "wdvi" "mean": 0.233799993991851
# Median is same as for median(r.sentinelhub.wgs84.wdvi.pol.vals,na.rm=TRUE)
# in csv corresponds with cellStats calculated from clipped tif!
# So while the tif returned is a non-clipped image, the downloaded statistics are from the clipped image
# Exactly as we wanted.
cellStats(r.sentinelhub.wgs84.wdvi,'countNA') # [1] 27896
ncell(r.sentinelhub.wgs84.wdvi) # [1] 272718
cellStats(r.sentinelhub.wgs84.wdvi,'countNA') / ncell(r.sentinelhub.wgs84.wdvi) # [1] 0.1022888 # 10% no data? doesn't show in the plot?
cellStats(r.sentinelhub.wgs84.wdvi.pol,'countNA') # [1] 57625
summary(r.sentinelhub.wgs84.wdvi.pol.vals) # shows the same: NA's: 57625
ncell(r.sentinelhub.wgs84.wdvi.pol) # [1] 272718
populationCount = ncell(r.sentinelhub.wgs84.wdvi.pol) - cellStats(r.sentinelhub.wgs84.wdvi.pol,'countNA')
populationCount # [1] 215093
# file satelliteStats_test_BvdTFieldlabG92_20220308.csv
# "wdvi" "populationCount": 214688
# similar but not same